phd data science salary

Phd In Data Science Salaries: What You Can Expect To Earn

A PhD in data science qualifies you for some of the most prestigious and high-paying jobs in tech. But exact salaries can vary significantly based on your specialization, industry, location and experience. Understanding the earning potential can help you evaluate if a PhD is worthwhile.

If you’re short on time, here’s the key takeaway: Data scientists with a PhD earn median salaries between $130,000 to $165,000, with top earners making $200,000 or more annually .

Average Salary Ranges for Data Science PhDs

When it comes to pursuing a PhD in Data Science, one of the key factors that potential students consider is the earning potential. Data Science is a rapidly growing field that offers lucrative career opportunities, and the salaries for professionals with a PhD in Data Science can be quite impressive.

National median salaries

The national median salary for individuals with a PhD in Data Science is around $120,000 per year. This figure represents the midpoint of the salary range, with some professionals earning significantly higher salaries based on their level of experience, expertise, and the industry they work in.

According to recent studies, data scientists with a PhD can earn anywhere between $90,000 to $180,000 per year, depending on various factors such as location, industry, and company size.

Salaries by major cities and regions

Salaries for data science PhDs can vary significantly based on the city or region in which you work. For example, major tech hubs like San Francisco, New York City, and Seattle tend to offer higher salaries due to the high demand for data scientists and the cost of living in these areas.

On the other hand, cities with a lower cost of living may offer slightly lower salaries.

According to a survey conducted by Glassdoor , the average salary for data scientists with a PhD in San Francisco is around $145,000 per year, while in New York City, it’s approximately $135,000 per year.

In contrast, in cities like Atlanta or Austin, the average salary might be around $120,000 per year.

Variance across industries and companies

The industry and company you work for also play a significant role in determining your salary as a data science PhD. Industries such as finance, healthcare, and technology tend to offer higher salaries due to the high demand for data-driven insights and analytics.

Big tech companies like Google, Facebook, and Amazon are known for offering competitive salaries to data science PhDs. On the other hand, start-ups and smaller companies may offer slightly lower salaries but provide other perks like equity or flexible work arrangements.

According to a study published by PayScale , the average salary for data science PhDs in the finance industry is around $150,000 per year, while in the healthcare industry, it’s approximately $140,000 per year.

However, it’s important to note that these figures can vary based on factors such as location, experience, and the specific role within the industry.

Factors That Influence Salary

Academic focus or specialization.

One of the key factors that influence the salary of a PhD in Data Science is their academic focus or specialization. Data Science is a vast field with various sub-disciplines, such as machine learning, artificial intelligence, big data analytics, and more.

Specializing in a high-demand area can significantly increase earning potential. For example, professionals with expertise in machine learning algorithms and predictive modeling are in high demand and can command higher salaries.

Industry and type of employer

The industry and type of employer also play a crucial role in determining the salary of a PhD in Data Science. Different industries have different demands for data scientists, and some industries, such as finance, healthcare, and technology, tend to offer higher salaries due to the complexity and volume of data they deal with.

Additionally, working for large companies or research institutions may lead to higher salaries compared to smaller organizations.

Cost of living and location

The cost of living and location can have a significant impact on the salary of a PhD in Data Science. Salaries can vary greatly depending on the region and city where the professional is employed. For instance, data scientists working in cities with a high cost of living, such as San Francisco or New York, may earn higher salaries to offset the higher expenses.

On the other hand, data scientists working in smaller cities or regions with a lower cost of living may have a lower salary.

Years of experience

Experience is another crucial factor that influences the salary of a PhD in Data Science. As professionals gain more experience and expertise in the field, their earning potential tends to increase. Data scientists with several years of experience may have a higher salary compared to those who are just starting their careers.

Additionally, professionals who have a track record of successful projects and achievements may be able to negotiate higher salaries.

Roles and Titles for PhDs

Obtaining a PhD in Data Science opens up a wide range of career opportunities. Let’s explore some of the roles and titles that PhD holders in this field can expect to pursue.

Data Scientist

The role of a data scientist is highly sought after in today’s data-driven world. Data scientists are responsible for collecting, analyzing, and interpreting large sets of complex data to uncover valuable insights and drive decision-making.

They use various statistical and machine learning techniques to develop models and algorithms that can predict future trends and patterns. According to Glassdoor , the average salary for a data scientist with a PhD is around $120,000 per year.

Research Scientist

A research scientist with a PhD in Data Science focuses on conducting advanced research and development in the field. They work on cutting-edge projects, exploring new algorithms, and developing innovative solutions to complex data problems.

Research scientists often publish their findings in academic journals and contribute to the advancement of the field. The average salary for a research scientist can range from $90,000 to $150,000 per year, depending on experience and industry.

Machine Learning Engineer

Machine learning engineers are responsible for designing, implementing, and maintaining the infrastructure and systems that power machine learning models. They work closely with data scientists and software engineers to deploy and scale machine learning algorithms in real-world applications.

Machine learning engineers also optimize and fine-tune models to improve their performance. According to Payscale , the average salary for a machine learning engineer with a PhD can range from $100,000 to $150,000 per year.

Analytics Lead/Director

As an analytics lead or director, PhD holders in Data Science take on managerial roles where they oversee data analytics teams and projects. They are responsible for defining the strategic direction of analytics initiatives, setting goals, and ensuring that projects are executed successfully.

Analytics leads/directors collaborate with cross-functional teams to identify business opportunities and develop data-driven strategies. The average salary for an analytics lead or director can range from $120,000 to $200,000 per year, depending on the size and industry of the organization.

These are just a few examples of the roles and titles that PhD holders in Data Science can pursue. The field is rapidly growing, and there is a high demand for skilled professionals who can leverage data to drive innovation and make informed decisions.

With the right skills and qualifications, a PhD in Data Science can open up exciting and lucrative career opportunities.

Career Advancement and Growth

Obtaining a PhD in Data Science can open up a world of career advancement and growth opportunities. With the increasing demand for data professionals in various industries, individuals with advanced degrees in data science are highly sought after.

Here are some ways in which a PhD in Data Science can propel your career:

Move into leadership/executive positions

One of the major benefits of having a PhD in Data Science is the opportunity to move into leadership or executive positions within an organization. With your advanced knowledge and expertise in data analysis and interpretation, you can take on roles such as Chief Data Officer or Data Science Director.

These positions often come with higher salaries and greater responsibilities, allowing you to have a significant impact on the strategic direction of the company.

Manage teams of data professionals

As a PhD holder in Data Science, you will have the ability to lead and manage teams of data professionals. This can involve overseeing the work of data analysts, data engineers, and data scientists, ensuring that projects are executed efficiently and effectively.

By managing a team, you can not only contribute to the success of the organization but also develop your leadership and managerial skills, which are highly valued in the industry.

Consulting and freelance opportunities

With a PhD in Data Science, you can also explore consulting and freelance opportunities. Many companies and organizations are in need of data experts to help them make sense of their data and provide insights for decision-making.

As a consultant or freelancer, you have the flexibility to work on a variety of projects with different clients, allowing you to continuously sharpen your skills and expand your network. This can lead to exciting and lucrative opportunities in the field.

According to a study conducted by Bureau of Labor Statistics , the demand for data scientists is projected to grow by 16% from 2020 to 2030, much faster than the average for all occupations. This indicates a promising outlook for those pursuing a career in the field of data science, especially for those with advanced degrees such as a PhD.

Other Benefits Beyond Salary

Expert status in a top field.

One of the major benefits of earning a PhD in Data Science is the expert status it confers upon you in a rapidly growing and highly sought-after field. With a PhD, you become a recognized authority in the world of data science, which can open doors to exciting career opportunities and prestigious positions.

Employers value the depth of knowledge and expertise that comes with a PhD, and this can lead to rewarding projects, collaborations, and leadership roles within organizations.

Opportunities for publications

Another advantage of pursuing a PhD in Data Science is the opportunity to contribute to the advancement of knowledge through research publications. As a PhD student, you will have the chance to conduct original research and publish your findings in reputable journals and conferences.

Publishing your work not only adds to the body of knowledge in the field, but it also enhances your professional reputation and can increase your chances of securing high-profile positions or academic research roles.

Additionally, having publications to your name can be a valuable asset when applying for grants and funding for future projects.

Job security and flexibility

Having a PhD in Data Science can provide a sense of job security and flexibility in the ever-evolving job market. Data scientists with advanced degrees are in high demand across industries, as organizations increasingly rely on data-driven insights to make strategic decisions.

The specialized skills and knowledge gained during a PhD program make you a valuable asset in industries such as technology, healthcare, finance, and consulting. Furthermore, the versatility of a PhD in Data Science allows you to explore various career paths, including academia, industry research, consulting, and entrepreneurship.

According to a survey conducted by Burtch Works , data scientists with PhDs tend to earn higher salaries compared to those with master’s degrees. However, it is important to note that the benefits of a PhD in Data Science extend beyond monetary compensation.

The expert status, opportunities for publications, and job security and flexibility that come with a PhD make it a worthwhile investment for those passionate about the field of data science.

A PhD in data science can unlock high-paying, advanced career opportunities in data and analytics. While salaries vary based on specialization, location, and employer, data scientists with doctoral degrees can expect to earn well into six figures.

Beyond competitive pay, a data science PhD also brings prestige, flexibility, and the chance to be a leader in an increasingly critical domain. Weighing salaries alongside other benefits can help determine if pursuing this advanced degree is the right move to maximize your career potential.

Similar Posts

Information Science Vs Data Science: How Are They Different?

With the exponential growth of data in the digital age, information science and data science have emerged as two exciting and in-demand fields. But what exactly do they involve, and how do they differ? Many looking to pursue careers in these areas find the overlap confusing. If you’re short on time, here’s a quick answer:…

Is Ap Environmental Science Hard? Evaluating The Rigor Of This Science Ap Course

For students interested in environmental issues and science, AP Environmental Science (APES) offers an appealing multidisciplinary course. Covering ecology, biology, geology, and more, APES explores the interrelationships within the natural world. But with scientific depth across many domains, some may wonder – is AP Environmental Science a difficult AP course compared to other science options?…

New York University Computer Science Program Rankings

As a globally recognized research university based in the tech hub of New York City, New York University (NYU) is home to one of the nation’s leading computer science programs. But how does NYU computer science measure up in major college rankings? In this comprehensive guide, we analyze NYU’s CS rankings across factors like research…

Double Majoring In Computer Science And Computer Engineering: The Pros And Cons

In today’s tech-driven world, computer science and computer engineering are two of the most in-demand fields. Many students consider double majoring in these complementary disciplines to expand their skillsets. If you’re short on time, here’s a quick answer: While challenging, double majoring in computer science and engineering allows you to gain expertise in software and…

The Science Of Human Behavior: An In-Depth Look

Understanding why people think, feel, and act as they do has long been a subject of fascination and study. Across history, philosophers, researchers, and scientists have sought to make sense of the mysteries of human nature. But what specific field focuses on analyzing and explaining human behavior using scientific methods? If you’re short on time,…

Is Data Science A Hard Major? The Complete Guide

Data science is one of the hottest and most in-demand fields right now. With starting salaries averaging over $95,000 a year, it’s no wonder so many college students are considering majoring in data science. If you’re short on time, here’s a quick answer to your question: Data science is generally considered a challenging major due…

Phd in Data Science Salary for 2024

Introduction.

A Ph.D. in data science doesn’t just offer a bump in salary, it’s increasingly becoming a required credential for the industry’s most prized jobs.

In fact, 79% of data scientists hold an advanced degree, and 38% hold a PhD. Similarly, for many experienced FAANG data science jobs, a Ph.D. is a preferred or required qualification.

Breaking down the Ph.D. in data science salary for 2023, we see results in a significant salary bump:

• The average PhD in data science salary is $172,045 .

If you’re contemplating if a data science PhD is worth it, you’ll likely recoup costs in yearly salary. Yet, there are additional advantages to pursuing a PhD, including advanced domain knowledge and research expertise.

Data Science PhDs Salary vs Master's

A Ph.D. in data science often results in some of the best-starting wages in tech. Here’s a comparison of data science salaries for PhDs vs. master’s degree holders:

Individual Contributor II

• Master’s : $123,313
• PhD : $139,857

In the top 75% of earners, the wage gap decreases to $140,000 (master’s) vs $150,000 (PhD).

Individual Contributor III

• Master’s : $150,304
• PhD : $172,262

In the top 75% of earners, the wage gap increases for more senior-level jobs, from $160,000 (master’s) to $189,000 (PhD).

Is a PhD in Data Science Worth It?

Here are some factors why a Ph.D. in Data Science may be worth it:

• New Technology - Many Ph.D. students are drawn to the challenge of solving new problems in machine learning, AI, computer vision, and robotics.
• Increasing Salaries - The earning potential of private industry jobs is a key driver.
• Need for Researchers - Companies need professionals with extensive research capabilities.

Does a Phd in Data Science Command a High Salary?

Data science PhD programs have become more and more common over the last five years. These programs offer highly specialized knowledge, and as a result, PhDs who specialize in data science can expect a significant earnings increase and will always be competitive for jobs, including senior-level management positions.

Yet, although career earnings might be more and the fact these programs can provide a competitive edge, there are some considerations that can make the decision less clear. They include:

• Cost : A Ph.D. in Data Science costs $1,300 per credit hour to $2,000 amount per credit hour. Ph.D. in Data Science programs require at least 60 - 75 credit hours, which will cost you up to $150,000 a year.
• Time Commitment : A PhD program typically requires 3-5 years of study, which can delay earnings. Master’s require as little as one year of study.

Ultimately, the worth of a data science PhD comes down to the type of work that you want to do. If you have an interest in research, you might consider a PhD.

Watch this video below on how much data scientists can make

Data Science PhD Salary vs Other Disciplines

Traditionally, those interested in a PhD for a data science career, choose a quantitative discipline, and in 2023, the most common were:

• Computer science (24%)
• Mathematics/statistics (21%)
• Natural science (21%)
• Engineering (19%)

Specific data science PhD programs are relatively new. For example, NYU launched its PhD program in 2017.

Therefore, there isn’t much data about salaries of data science PhDs vs economics PhD salaries , for instance. But these programs do offer some advantages, including highly specialized domain knowledge (like machine learning, causal inference or advanced analytics) and potential more established career networks.

Ultimately, no matter the field you choose, a PhD offers advanced training that results in a significant increase in salary, job competitiveness in the industry, and specialized knowledge at the forefront of data science.

Other top PhD fields for data science include statistics PhDs and decision science PhDs .

Build a Career You'll Love

Data science phd salary in the united states.

How much does a Data Science Phd make in the United States? The salary range for a Data Science Phd job is from $116,319 to $147,304 per year in the United States. Click on the filter to check out Data Science Phd job salaries by hourly, weekly, biweekly, semimonthly, monthly, and yearly.

• Per semimonth
• Connecticut
• District of Columbia
• Massachusetts
• Mississippi
• North Carolina
• North Dakota
• New Hampshire
• Pennsylvania
• Rhode Island
• South Carolina
• South Dakota
• West Virginia
• San Francisco, CA
• Washington, DC
• Chicago, IL
• New York, NY

HOW SHOULD YOU USE THIS DATA?

Employees: Use this as a guide for salary expectations, but be aware that responsibilities can change across companies for the same job title, so there may be differences between this data, other free site and our subscription products bought by employers.

Employers: This data could be used as reference point in your market pricing, but not the only source, due to differences across jobs locations, and sizes of companies.Consider additional sources like our Employer reported data.

Our consulting team crafts efficient, data-driven solutions using the power of CompAnalyst ® , ensuring your challenges are met head-on.

The trusted data and intuitive software your organization needs to get pay right.

Let our management tool - JobArchitect™ streamline your job description process. Say goodbye to the hassle of crafting job descriptions.

What Should I Pay?

Highest Paying Cities for Data Science Phd in the United States

States with Higher Salaries for Data Science Phd

How much do similar professions get paid in the united states, how much should you be earning, what does a data science phd do.

The issue that some data science PhD holders are reporting, especially in industry settings, is that that the state of the art is moving so quickly, and that the data science industry is evolving so rapidly, that an abundance of research oriented expertise is not always what’s heavily sought after.

Historically, data science PhD programs were one of the main avenues to get a good data-related position in academia or industry.

The guide will walk through some of the key considerations while picking graduate data science programs and some of the nuts and bolts (like course load and tuition costs) that are part of the data science PhD decision-making process.

At the end of a day, whether a data science PhD is worth it will be entirely dependent upon your personal interests and career goals.

View Job Skills and Competency Data for more than 15,000 Job Titles, 18 Industries, and 26 Job Families.

Most Common Benefits for Data Science Phd

Related companies for data science phd in the united states, frequently asked questions, do i receive fair pay as a data science phd currently, what are the responsibilities of a data science phd, how much do similar jobs to data science phd make.

• Phd Computer Science
• Phd Material Science
• Data Scientist Phd
• Head of Data Science
• Data Science Consultant
• Data Science Engineer
• Analyst, Data Science
• Data Science And Analytics
• Data Science Associate

Where can I get a higher Data Science Phd salary in the United States?

What is the data science phd's salary range in the united states, career insights.

DiscoverDataScience.org

Is a PhD in Data Science Worth It?

Created by aasif.faizal

The most advanced option you can find is a Data Science PhD, which is an intensive and long-term commitment from which you will graduate at the very top of your field.

The truth is, many who establish thriving careers in data science don’t hold PhDs, and no one would argue that they are necessary to have on the table as one considers their educational options. Estimates for the number of data science PhDs is around one third of all who attend graduate school for data science. For a certain type of person – one who is highly studious, with an aptitude for and interest in research – PhD programs can be excellent experience that will situate you for a highly specialized career.

If you’re asking yourself, “Do I need a PhD in Data Science?,” the answer is no. (For a more expansive answer to this question, you can take a look at our article here: “Do I need a PhD in Data Science?”)

But is a PhD in Data Science worth it for those who do decide to take it on? The answer, in short, is yes – at least, it can be. This article will explain the greatest rewards of taking on a doctorate program, with information about job options, Data Science PhD salary ranges, and job growth projections. To learn about all of those as well as survey the other degree options for data scientists, read on.

Advantages of a Data Science PhD

So if a PhD in Data Science isn’t necessary to building a high-earning career in big data, what are the advantages of taking on so many years of schooling? To put it simply, the answer is peerless expertise.

It’s true: one can hold just a master’s degree and still find excellent job opportunities in the data sciences, which is why master’s programs are the most popular path for those in the profession. However, it is unquestionable that a doctorate asserts a higher level of mastery and capability than even master’s degree holders have. If you apply for a job with a PhD on your resume, you’ll be instantly asserting that you are as knowledgeable as they come, which in the case of top-ranking (and top-earning) data science positions is exactly what companies are looking for.

Data Science PhD Programs: How They Work

If you think a doctoral degree in Data Science sounds like the right path for you, it’s worth learning about the specifics of a PhD program. Below is an overview of coursework, anticipated duration, and more.

Coursework and Duration

One of the primary differences between a data science PhD and a master’s program is that a doctorate program culminates in testing and a dissertation, while a master’s program does not. Courses in both programs typically include the following:

• Artificial intelligence
• Data management
• Data mining
• Data visualization
• Machine learning
• Software design

Data science PhDs are known for having an especially intensive orientation toward research, especially in the dissertation component of the work. This can extend the duration of a PhD program by several years. While master’s programs typically take two years if students attend them full-time, a PhD program typically adds two or three years of studying to that timeline.

While many who pursue data science PhDs argue that the insight gained from their extensive dissertation work has paid off in the long run, it’s important to ask yourself if you are going to enjoy making such a deep dive into your studies. If the answer is yes, that’s an excellent reason to proceed with your PhD degree. If not, a master’s program may be the more optimal path for you.

The testing process for data science PhDs is also rigorous, with multiple exams along the way to prove competencies in a variety of subjects. These include oral, written, and practical exams. Earning a PhD asserts by default that you have achieved the mastery needed to pass these tests, which is a powerful assertion of your skill and ability from the get-go.

Finding Your Area of Focus

Like with master’s programs, those pursuing data science degrees typically choose a particular area of focus while in school that will lead directly to their professional specialization. This means it’s crucial to get the lay of the land early so that you’re sure you’re picking a path you’re willing to commit to for a long time. (It’s always possible to acquire deeper insight or even pursue new specialties through certification programs, but it’s recommended to start with one focus that tracks with a degree concentration offered by your school.)

Data Science Salaries

The vast field of data science is proving to be an exceptionally fertile ground to grow a career, no matter what focus area you choose. Indeed, according to the Bureau of Labor Statistics , the median annual pay for data scientists overall is an impressive $100,910 per year, well ahead of most other industries. This is an excellent reason to join this burgeoning field, and it’s been enough to motivate droves of people to pursue data science careers of their own.

If you’re impressed by these numbers, consider this: those statistics describe the overall field of data science, not just the jobs of those who hold PhDs. For these highly advanced professionals, the numbers get much higher. Take a look at the job titles in the next section to see the specific wages of high-ranking data science positions.

While the sudden rush of new candidates seeking data science positions may sound daunting, the job growth statistics for data scientists all but guarantee that high-quality jobs will be available in your area of focus. This is because of the exceptional projected growth rate of data science jobs, which the Bureau of Labor Statistics estimates to be an incredible 36% by 2031.

There are few other industries that offer as significant salaries across the board with so many new positions available.

So why are data scientists so in-demand, and why is the field growing so rapidly? The answer has everything to do with the rise of technology in all aspects of our lives, in particular the way it has transformed how we do business. The rate at which new data technology is evolving means constant adaptations within the world of big data to keep up with it. For example, recent leaps in the field of machine learning (ML) has greatly increased data capturing capacities, leading to a greater need for specialized data analysts who can help process the information quickly.

Careers for Data Science PhDs

One of the biggest questions for prospective data science PhD candidates is this: what will it lead to? Indeed, given the rigor of a data science PhD program, it’s important to think through the investment you’re making.

Below are some of the most common positions data scientist PhDs pursue, along with data scientist PhD salary ranges and more.

High Level Data Scientist

Data scientists often pursue more focused concentrations in the field, but their overall functions include collecting and categorizing data so that it can best be leveraged by organizations. Those who hold doctorate degrees in data science are often available for the highest levels of these jobs, which are roles responsible for important decision making functions, oftentimes communicating with executives and other heads of staff on the key insights they’ve acquired in their field.

As you might expect, these high-ranking data science roles earn significant amounts of money. According to the Bureau of Labor Statistics, data scientists earning in the 90th percentile of the field make an annual mean wage of $167,040.

Business Analyst

Business analysts, also often known as management analysts or management consultants, use advanced algorithms to analyze and interpret data that will later be used to guide business strategy. These can be in-house roles at large organizations or consultant positions who are contracted independently on a project basis. Those who excel at business are especially good candidates to pursue this career path.

According to the Bureau of Labor Statistics, management analysts working at the top of their field (in the 90th percentile) earn an annual mean wage of $163,760.

Database Architects

Database architects play a huge role in a business’ data practices, serving as exactly what their name implies – architects who create the virtual structure in which data is stored and organized. It’s imperative that those who hold these roles be highly advanced in their field, as the strength of a business’ database is a crucial factor in the success of its overall operations.

Database architects are highly valued employees and are compensated accordingly. The Bureau of Labor Statistics reports that the top earning database architects in the US make a mean annual wage of $169,500.

Information Security Analysts

The field of cybersecurity is rapidly expanding as new technologies also introduce new types of cyberattacks to databases. Those with rigorous specialization in information security – such as what is conferred by a data science PhD – are ideal candidates to fill these roles. Indeed, companies are unlikely to hire anyone who is not seriously qualified to do this role, as this person will take responsibility for protecting the business’ most vital documents.

The highest earning (90th percentile) information security analysts are reported by the Bureau of Labor Statistics to make a mean annual salary of $165,920.

Other Data Science Degree Options

Now that you understand the benefits of a data science PhD program, it’s worth taking stock of the other data science degree and certification options that are available. Good news: all of these degree types have online options, many of which are part-time. This means you can attend school from anywhere, with any schedule.

Data Science Bachelor’s Degree

If you would like to pursue a data science PhD but don’t yet hold a bachelor’s degree in any subject, you will first need to complete a bachelor’s program. If you are in this position, it’s recommended to concentrate on data science during undergraduate school so that you can get a rich introduction to the field, even perhaps finding the area of focus where you’d like to plan your career.

It is possible to start a career in data science with just a bachelor’s degree, though most elect to pursue some level of graduate program, as you will enter the field at a higher level of responsibility, with pay to match. To learn more about bachelor’s in data science degree programs, take a look at our guide here .

Data Science Master’s Degree

A master’s in data science is the most popular path for those entering the field of big data. This degree will give you the expertise needed to find competitive jobs with significant responsibilities and the excellent salaries that draw so many to the data science profession. The coursework for a master’s degree is quite similar to a PhD, minus the intensive testing and the dissertation.

There are numerous fantastic Master’s in Data Science programs that can give you the experience and education needed to find a great position in the field. When choosing a master’s program, be sure it offers a concentration in your intended area of specialty. To take a look at the top online master’s programs available near you, visit our guide here .

Data Science Associates Degree

If you do not have a bachelor’s degree and would like to get your professional life started quickly, an associates degree program can give you the training you need to pursue some entry-level jobs in the world of data science. It’s important to note that these programs on their own are unlikely to give you the expertise needed for a high-earning data science career, but they can offer excellent exposure to the field and provide you with your first work experience.

To learn more about associates in data science degree programs, enjoy our guide here, which will give you all the information you need.

Data Science Certificate

An alternative to a long-term degree program, data science certificates can build a particular area of skill or expertise that can help situate you on a particular career path in data science. Some data science professionals who hold advanced degrees also decide to take on certificate programs to expand on their areas of knowledge or add to their list of specializations.

To learn more about data science certificate programs, visit our comprehensive guide here .

Data Science Bootcamps

Data science bootcamps are likely the fastest possible way to enter the data science profession. These courses – which usually have remote and in-person options – give you a literal crash course in a particular arena of data science, typically over a period of about twelve weeks. You will leave with a developed skill set that usually tracks with a particular type of entry-level job.

Like with most data science opportunities outside of graduate programs, these bootcamps are unlikely to set you up with a high-ranking data science careers, but they can be an excellent way to build your fluency in programming languages or other data science skills.

Data science bootcamps are booming, with plenty of options all over the country. Take a look at our guide here to find the program that is right for you.

Finding the Path That’s Right for You

If you’re feeling overwhelmed by the different opportunities available in the data sciences, don’t worry. While there are indeed many options that are suited to candidates with different skill sets, interests, and backgrounds, the good news is that most of these options are good, and are likely to significantly help you start your career.

For a more elaborate overview of the different program options in data science, take a look at our program guide here for a complete comparison.

• Related Programs

Data Scientist salary in US

Average base salary in us, how much does a data scientist make in us.

The average salary for a Data Scientist in US is $125,446. The average additional cash compensation for a Data Scientist in US is $16,878. The average total compensation for a Data Scientist in US is $142,324. Data Scientist salaries are based on responses gathered by Built In from anonymous Data Scientist employees in US.

Salary Insights

Best-paying cities for data scientist.

Data Scientist Salary by gender

Data scientist salary by years of experience, data scientist salary ranges, average data + analytics salaries in us.

What is a data scientist?

How to become a data scientist, how much does a data scientist make.

The salary range for a data scientist is $50K-$345K. The average salary for a Data Scientist in US is $125,446.

Career Info

Data scientist jobs in us, skills that affect data scientist salaries in us, average data scientist salary by company size, recent data scientist salaries in us.

• Data Scientist

Google Data Scientist Salaries

Data Scientist compensation in United States at Google ranges from $148K per year for L3 to $881K per year for L8. The median compensation in United States package totals $276K. View the base salary, stock, and bonus breakdowns for Google's total compensation packages. Last updated: 9/8/2024

Average Compensation By Level .css-s9ggwg{z-index:1500;pointer-events:none;}.css-s9ggwg[data-popper-placement*="bottom"] .MuiTooltip-arrow{top:0;margin-top:-0.71em;}.css-s9ggwg[data-popper-placement*="bottom"] .MuiTooltip-arrow::before{transform-origin:0 100%;}.css-s9ggwg[data-popper-placement*="top"] .MuiTooltip-arrow{bottom:0;margin-bottom:-0.71em;}.css-s9ggwg[data-popper-placement*="top"] .MuiTooltip-arrow::before{transform-origin:100% 0;}.css-s9ggwg[data-popper-placement*="right"] .MuiTooltip-arrow{left:0;margin-left:-0.71em;height:1em;width:0.71em;}.css-s9ggwg[data-popper-placement*="right"] .MuiTooltip-arrow::before{transform-origin:100% 100%;}.css-s9ggwg[data-popper-placement*="left"] .MuiTooltip-arrow{right:0;margin-right:-0.71em;height:1em;width:0.71em;}.css-s9ggwg[data-popper-placement*="left"] .MuiTooltip-arrow::before{transform-origin:0 0;}

Given Google sometimes issues offers with an irregular vesting schedule (33%, 33%, 22%, 12%), the average total compensation is calculated by dividing the total stock grant evenly by 4

Latest Salary Submissions

Vesting Schedule

At Google, Main RSUs are subject to a 4-year vesting schedule:

38 % vests in the 1st -year ( 3.17 % monthly )

32 % vests in the 2nd -year ( 2.67 % monthly )

20 % vests in the 3rd -year ( 1.67 % monthly )

10 % vests in the 4th -year ( 0.83 % monthly )

33 % vests in the 1st -year ( 2.75 % monthly )

33 % vests in the 2nd -year ( 2.75 % monthly )

22 % vests in the 3rd -year ( 1.83 % monthly )

12 % vests in the 4th -year ( 1.00 % monthly )

Google commonly refers to RSU as GSU (Google Stock Unit). Although the name is different, it is the same as RSU's. Google's Vesting Schedule may vary between monthly and quarterly vesting depending on the number of shares you recieve: less than 32 GSUs (Annually), 32 - 63 GSUs (Semi-annually), 64 - 159 GSUs (Quarterly) and 160+ GSUs (Monthly).

50 % vests in the 1st -year ( 4.17 % monthly )

28 % vests in the 2nd -year ( 2.33 % monthly )

12 % vests in the 3rd -year ( 1.00 % monthly )

36 % vests in the 1st -year ( 3.00 % monthly )

16 % vests in the 4th -year ( 1.33 % monthly )

25 % vests in the 1st -year ( 2.08 % monthly )

25 % vests in the 2nd -year ( 2.08 % monthly )

25 % vests in the 3rd -year ( 2.08 % monthly )

25 % vests in the 4th -year ( 2.08 % monthly )

25 % vests in the 1st -year ( 6.25 % quarterly )

25 % vests in the 2nd -year ( 6.25 % quarterly )

25 % vests in the 3rd -year ( 6.25 % quarterly )

25 % vests in the 4th -year ( 6.25 % quarterly )

At Google, Main RSUs are subject to a 3-year vesting schedule:

33 % vests in the 1st -year ( 8.25 % quarterly )

33 % vests in the 2nd -year ( 8.25 % quarterly )

34 % vests in the 3rd -year ( 8.50 % quarterly )

Get Verified Salaries in your Inbox

Subscribe to verified Data Scientist offers. You’ll get the breakdown of compensation details by email. Learn More →

Featured Jobs

Related Companies

• See all companies ➜

Other Resources

• End of Year Pay Report
• Calculate Total Comp

Doctor of Philosophy in Data Science

Developing future pioneers in data science

The School of Data Science at the University of Virginia is committed to educating the next generation of data science leaders. The Ph.D. in Data Science is designed to impart the skills and knowledge necessary to enable research and discovery in data science methods. Because the end goal is to extract knowledge and enable discovery from complex data, the program also boasts robust applied training that is geared toward interdisciplinary collaboration. Doctoral candidates will master the computational and mathematical foundations of data science, and develop competencies in data engineering, software development, data policy and ethics. 

Doctoral students in our program apprentice with faculty and pursue advanced research in an interdisciplinary, collaborative environment that is often focused on scientific discovery via data science methods. By serving as teaching assistants for the School’s undergraduate and graduate programs, they learn to be adroit educators and hone their critical thinking and communication skills.

LEARNING OUTCOMES

Pursuing a Ph.D. in Data Science will prepare you to become an expert in the field and work at the cutting edge of a new discipline. According to LinkedIn’s most recent Emerging Jobs Report, data science is booming and data scientist is one of the top three fastest growing jobs. A Ph.D. in Data Science from the University of Virginia opens career paths in academia, industry or government. Graduates of our program will:

• Understand data as a generic concept, and how data encodes and captures information
• Be fluent in modern data engineering techniques, and work with complex and large data sets
• Recognize ethical and legal issues relevant to data analytics and their impact on society 
• Develop innovative computational algorithms and novel statistical methods that transform data into knowledge
• Collaborate with research teams from a wide array of scientific fields 
• Effectively communicate methods and results to a variety of audiences and stakeholders
• Recognize the broad applicability of data science methods and models 

Graduates of the Ph.D. in Data Science will have contributed novel methodological research to the field of data science, demonstrated their work has impactful interdisciplinary applications and defended their methods in an open forum.

A Week in the Life: First-Year Ph.D. Student

Ph.D. Student Profile: Jade Preston

Ph.D. Student Profile: Beau LeBlond

Get the latest news.

Subscribe to receive updates from the School of Data Science.

• Prospective Student
• School of Data Science Alumnus
• UVA Affiliate
• Industry Member

Request More Info

Fill out the form below and a member of our team will reach out right away!

" * " indicates required fields

Data Science

Data Scientist Salaries — High Pay in an Exciting, In-Demand Field

Data Scientist Salaries Overview

Data scientist salaries by experience, data scientist salaries by industry, data scientist salaries by region, data scientist salaries by state, data scientist salaries at top companies, data scientist salaries by education, how to boost your salary in data science.

In addition to driving innovation across nearly all industries, data science is a field that pays high salaries to the skilled professionals who understand how to discover valuable insights hidden amid vast amounts of raw information.

Despite recent disruptions in all employment sectors caused by the COVID-19 crisis, a leading-edge study of the data science employment landscape reports, “We are still seeing fierce competition for top tier talent, with many in-demand candidates receiving multiple offers quickly.”

The following information on data science salaries comes from a survey of more than 500 data science professionals conducted by executive recruiting and staffing firm Burtch Works, the U.S. Bureau of Labor Statistics, plus additional sources. Read on for a deep dive into data science salaries, salary growth, data science salaries by region and by industry, data science salaries with a master’s or Ph.D., and more.

Simply stated, data scientists earn high salaries. The U.S. Bureau of Labor Statistics reports  median salaries of $108,020 , with the top 10% earning more than $184,090. The bureau also projects a 35% hiring growth rate through 2032 .

The 2023 Burtch Works salary survey reports base median salaries from $100,400 to $252,900 depending on years of experience and, for data science managers, level of responsibility. It is important to note that salary figures here represent gross annual wages and do not reflect additional compensation and financial incentives such as relocation assistance, sign-on bonuses, annual bonuses, stock options, or other long-term incentive plan compensation.

View this post on Instagram

A post shared by Salary Transparent Street (@salarytransparentstreet)

As in many professions, salaries get higher depending on your level of experience. The Burtch Works study breaks down the following six different categories of data scientists and data science managers based on years of experience and level of managerial responsibility, respectively:

Data Scientist | Level 1 (0-3 years of experience)

Data Scientist | Level 2 (4-8 years of experience)

Data Scientist | Level 3 (9+ years of experience)

Data Science Manager | Level 1 (supervises 1-3 people)

Data Science Manager | Level 2 (supervises 4-9 people)

Data Science Manager | Level 3 (supervises 10+ people)

Respondents to the survey from the above categories reported the following median base salary ranges:

Data Scientist | Level 1 ($85,000–$110,000)

Data Scientist | Level 2 ($120,000–$140,000)

Data Scientist | Level 3 ($148,000–$185,000)

Data Science Manager | Level 1 ($132,000–$164,000)

Data Science Manager | Level 2 ($180,000–$210,000)

Data Science Manager | Level 3 ($210,000–$275,000)

According to the study, “Data science continues to be a young discipline with median years of experience (equaling) 6 years.”

[Webinar] WATCH: Data Science Careers Webinar [Key Info About an Extraordinary Opportunity] >>

Because data science’s capacity to discover valuable insights and help solve business challenges touches nearly every sector, there is a strong demand for qualified data scientists across a broad spectrum of industries. Key sectors with an ongoing need for data scientists include:

Technology | Financial Services | Health Care | Cybersecurity | Government/Military | Academia | Media | Retail | Manufacturing | Energy

The many additional areas now impacted by data science include: marketing, aerospace, travel, transportation, energy, food, sales and service, business intelligence, agriculture, automotive, mining, field service, utilities, telecom, construction, and more.

Here is a closer look at the Burtch Works survey’s breakdown of the percentage of data scientists working in various industries:

Technology (plus Telecom/Gaming) — 26%

Corporate (plus Energy/Manufacturing) — 21%

Financial Services — 13%

Consulting — 13%

Retail & CPG — 7%

Health Care/Pharma — 11%

Advertising/Marketing — 6%

Academic/Government — 3%

Source: Burtch Works Study (2018)

Data scientists working on the West Coast reported the highest median base salaries in the Burtch Works survey, with those in the Northeast earning more than their high-tech counterparts in the nation’s midsection.

You can also find interesting data about the data science employment landscape at employment sites such as ZipRecruiter, Glassdoor, Indeed, and others. (Note: Salary-by-state data typically does not account for years of experience.)

Springboard.com lists California as having the highest average salary for data scientists at $142,338. ZipRecruiter’s review of data scientist salaries by state places New York ($130,980) and Massachusetts ($129,742) in the top spots.

This category is a bit of a moving target, but tech training company Galvanize offers the following list of “10 top-paying companies for data scientists in 2020.”

• Snap, Inc. — $238,000
• Airbnb — $223,000
• Netflix — $222,000
• Pinterest — $212,000
• Lyft — $209,000
• Etsy — $207,000
• Uber — $206,000
• Facebook — $198,000
• Twitter — $198,000
• Dropbox — $183,000

Level of education is another critical factor when it comes to salaries in data science, a field where the vast majority of practitioners hold advanced degrees. The Burtch Works survey puts this figure at 94% — with 50% having earned at least a master’s degree and 44% holding a Ph.D.

(Additionally, the report notes that 25% of data scientists hold a degree in statistics or mathematics, 22% have a computer science degree, 16% hold a degree in the natural sciences, and 24% hold an engineering degree.)

Here is a look at survey results with the level of education factored in:

Source: Burtch Works Study (2020)

Data scientists are in demand, but competition is strong for the best, highest-paying jobs. Therefore, one of the first steps when exploring the data science job market is to do some in-depth salary research on websites such as Glassdoor, LinkedIn, and others to help get a clear idea of your market value.

Statistics about data science salaries by region, by industry, and education level all offer insight into possibilities for earning higher pay. But it is also helpful to keep in mind that part of the role for many data scientists is that of the storyteller — presenting data-driven insights that help solve business challenges in a way that is understandable to decision-makers.

So look for ways to effectively tell your own story to prospective employers in the interview process. Rather than just listing off skills and experience, look for ways to talk about what inspires you about data science or share an anecdote about your journey as a data scientist.

As mentioned above, it’s no secret that the vast majority of data scientists hold an advanced degree. If you are considering earning your master’s degree to pursue or advance a career in data science, or if you are seeking a data science master’s program to complement an advanced degree in another discipline, you may want to take a close look at the innovative, online master’s degree program offered by the University of San Diego.

Providing optimal flexibility for busy working professionals, USD’s Master of Science in Applied Data Science is taught by experienced data science practitioners and tailored to the needs of industries and employers.

Students gain comprehensive technical knowledge and skills, while developing a deep understanding of how to apply both hard and soft skills in real-world applications in a top-quality degree program designed to position graduates for career success — and high salaries — in this vitally important and fast-growing field.

[RELATED] University of San Diego Launches Online Master’s Degree in Applied Data Science

Be Sure To Share This Article

• Share on Twitter
• Share on Facebook
• Share on LinkedIn

Considering Earning Your Master’s in Data Science?

Free checklist helps you compare programs, select one that’s ideal for you.

• Master of Science in Applied Data Science

Related Posts

Artificial Intelligence

The Salaries Of Data Scientists Remain Steady But Still Sexy With AI On The Horizon

Shutterstock

The just-published 5th-annual Burtch Works Study: Salaries of Data Scientists provides fresh insights into the compensation trends for those holding the sexiest job of the 21 st century :

• Similar to last year’s figures, the median base salaries of data scientists have remained relatively steady. After rising rapidly in 2015 and 2016, median base salaries at all job levels changed by a single-digit percentage point or not at all from March 2017 to March 2018.
• The median base salaries range from $95,000 at level 1 (0-3 years of experience) to $165,000 at level 3 (9+ years) for individual contributors and from $145,000 at level 1 (1-3 reports) to $250,000 at level 3 (10+ reports) for managers.

Data Scientists Salaries 2018

• If you are a data scientist, you don’t need to become a manger to earn a high salary. Becoming a subject matter expert can be a separate career track that doesn’t have to lead to people management.
• Data scientists holding a PhD earn higher median base salaries than those holding a Master’s degree in every job category. This trend is most pronounced among individual contributors—at level 1, data scientists with a PhD earn a median base salary of $102,000 while those with a Master’s degree earn a median base salary of $92,500.
• Data scientists earn base salaries up to 36% higher than other predictive analytics professionals. In all job categories except the higher-level managers, data scientists realize a double-digit percentage advantage in base salary compared to others in predictive analytics. (Burtch Works distinguishes data scientists from other predictive analytics professionals by “the depth and breadth of data scientists’ coding skills,” allowing them “to exploit data regardless of its source, size, or format.”)
• The salary gap between data scientists working for technology companies and those in other industries is beginning to narrow. Yet another indicator that today, all companies are tech companies…
• Previously, H-1B residency status held constant at 9% (2015 and 2016) and 8% (2017) of the data scientists covered by the Burtch study, but this year’s data shows a jump to 13% of data scientists holding an H-1B visa. This may be due, says Burtch, “to many companies realizing that it is important to employ an aggressive hiring strategy for data science and gain access to a wider talent pool by supporting the visa transfer process. Additionally, the lengthening green card process could be at play.”

Sexy salaries attract new entrants into a new profession and a new profession evolves to accommodate the increasing demand for its services. There has been a shift to requiring Master’s degrees instead of PhD’s which in turn helped drive the proliferation of data science Master’s programs . The pool of available data scientists has increased due to the influx of existing statisticians and analytics professionals upgrading their skills (and their job descriptions) and newly-minted graduates of data science educational programs (including many online courses).

The supply of data scientists has increased, but so has the demand. As a result, salary growth has moderated but the salaries offered to data scientists still remain at the “sexiest” level. Confirming the Burtch study in this regard, is an analysis conducted by Web data provider PromptCloud , exclusive to Pressed Data . Analyzing job listings for data scientists on Dice.com in July 2017 and March 2018, PromptCloud has found that the average salary offered has increased 6.43%.

Data Scientists' Average Salary 2017-2018

The job listings also confirm the Burtch study’s contention that data scientists are distinguished from other analytics professionals by their coding proficiency. An analysis of the required skills listed in these jobs descriptions shows that the Python programming language leads by a wide margin other popular statistical analysis, data management, and coding tools.

Data Scientists: Top Required Skills

Python was first implemented in the late 1980s, but it was its 3 rd version, released 10 years ago, that became—with the rise of “big data”—a widely popular tool among data scientists. Computer programming skills, especially in Python, contributed to the emerging definition and institutionalization of the new discipline, and with it, specialized training programs and how they were differentiated from their immediate predecessors, the “business analytics” programs.

One such new program was the Master of Data Science program at the Illinois Institute of Technology (IIT). Shlomo Argamon , Professor of Computer Science at IIT and director of the program from its inception five years ago, has also observed the broadening of both the demand for and the supply of data scientists. Says Argamon:

“The awareness of the usefulness of data science has grown, and as tools become more widely available, companies in a greater variety of industries are making use of data scientists, either in-house or via a growing number of data science consulting firms.”

And as the Burtch study also noted, Argamon has increasingly seen the graduates of the IIT program finding employment not only with tech firms and data science consultancies, but also “in a wide variety of industries such as insurance, media, manufacturing, banking, and more.” And he adds: “I should note that, despite the hype, it seems that most firms understand that they cannot just plug in some tools and expect results, that they need actual data scientists to get the insights they seek.”

The increase in the diversity of employment opportunities has been matched by the increasingly varied background of the people entering the data science profession. Argamon: “We’ve always sought a diversity of backgrounds among our students, as we see that as strengthening the learning experience for budding data scientists – our goal is to produce well-rounded data scientists who can effectively communicate with both technical and non-technical colleagues and clients, and who can learn new domains and collaborate with diverse experts.”

Over the last five years, Argamon has observed the growing attraction of data science to entrants from many different disciplines and experiences: “While our earliest students were almost entirely from computer science, engineering, and statistics backgrounds, we have seen growth in the numbers of our incoming students from other backgrounds, with majors such as business, history, biology, chemistry, economics, and anthropology. These different ways of thinking, we believe, will contribute to the breadth and effectiveness of these students and others in their cohort as data scientists.”

At IIT, as in similar data science programs, an integral part of the curriculum is practical experience. In addition to putting to test in real-life situations what they have learned in the classroom, these experiences highlight to the students (and would-be students) the value of data science for business and society.

In 2016, IIT’s basketball coach, Todd Kelly, turned to the data science program for help in what was probably the very first use of Moneyball -type methods in Division III sports. In 2013, IIT’s record was 0-25 and the next year, Kelly’s first as a coach, it improved to 2-23. After two IIT data science students spent the summer of 2016 collecting and analyzing data about the team, the IIT Scarlet Hawks finished the next season with a 22-6 record, making it all the way to the U.S. Collegiate Athletic Association Division 1 National Basketball Championship.

This kind of results make data scientists happy about the work they do. A recent KDnuggets job satisfaction survey found “that while Data Scientist may no longer be the sexiest profession, it is still very satisfying.” The jobs with the highest satisfaction, KDnuggets reports, are Machine Learning Engineer, Researcher/ Professor, and Data Scientist/Statistician. Is this a leading indicator that “machine learning” is the next “data science” in terms of sexiest salaries, satisfaction, and skill shortage?

Job Satisfaction by Position (Bar width corresponds to the number of respondents)

Burtch Works reports that they see a shift in job requirements toward machine learning and AI skills: “Now that many teams have grown, the need for generalist ‘unicorns’ has given way to a higher demand for data science specialists that can work with other analytics professionals and data engineers on the team. For example, we now regularly receive requests for experts in specific areas such as NLP (natural language processing) or image processing using tools like TensorFlow.”

AI specialists already command super-sexy salaries and the latest in machine learning and artificial intelligence is being added to data science training and career transition programs such as Insight Data Science . And so goes the cycle of evolving disciplines and job categories, all attempting to improve the methods and tools for data analysis and for finding new uses for computer-generated data.

Get the Reddit app

Wiki has been Updated!

A space for data science professionals to engage in discussions and debates on the subject of data science.

[Official] 2023 End of Year Salary Sharing thread

This is the official thread for sharing your current salaries (or recent offers).

See last year's Salary Sharing thread here . There was also an unofficial one from two weeks ago here .

Please only post salaries/offers if you're including hard numbers, but feel free to use a throwaway account if you're concerned about anonymity. You can also generalize some of your answers (e.g. "Large biotech company"), or add fields if you feel something is particularly relevant.

Tenure length:

Company/Industry:

Prior Experience:

$Internship

Relocation/Signing Bonus:

Stock and/or recurring bonuses:

Total comp:

Note that while the primary purpose of these threads is obviously to share compensation info, discussion is also encouraged.

By continuing, you agree to our User Agreement and acknowledge that you understand the Privacy Policy .

Enter the 6-digit code from your authenticator app

You’ve set up two-factor authentication for this account.

Enter a 6-digit backup code

Create your username and password.

Reddit is anonymous, so your username is what you’ll go by here. Choose wisely—because once you get a name, you can’t change it.

Reset your password

Enter your email address or username and we’ll send you a link to reset your password

Check your inbox

An email with a link to reset your password was sent to the email address associated with your account

Choose a Reddit account to continue

45,000+ students realised their study abroad dream with us. Take the first step today

Here’s your new year gift, one app for all your, study abroad needs, start your journey, track your progress, grow with the community and so much more.

Verification Code

An OTP has been sent to your registered mobile no. Please verify

Thanks for your comment !

Our team will review it before it's shown to our readers.

PhD in Data Science

• Updated on  
• Dec 6, 2023

If you’re interested in working independently in research fields after completing a master’s in mathematics, statistics , science, etc, then pursuing a PhD may be the right choice for you. It offers many reputed career choices along with satisfaction. The field is continuously growing and top companies Microsoft, Wipro, HCL, etc, are demanding data science graduates. So, read about PhD in Data Science to know about the course, its duration, after options, salary, top recruiting companies, and more.

This Blog Includes:

What is a phd in data science, eligibility criteria, list of top universities offering phd in data science abroad, universities offering phd in data science in india, researchers , college professors , senior data scientist, business analysts, machine learning professionals, average salary for phd graduates, top companies hiring data science graduates.

A PhD in Data Science gives students an edge and provides them with relevant knowledge in the fields like AI, Statistics, Machine Learning , Data Analysis, and the list goes on. Like all other PhD-level courses, it enables students to work independently in research fields and helps them apply both their practical and theoretical knowledge in data models.

Also Read: Fully-Funded PhD Programs

A PhD in Data Science has emerged as one of the leading courses as it enhances the career prospects of the candidates providing them with research and in-depth academic knowledge. Different universities have different specific criteria for admission that has to be met by the candidates. The basic eligibility requirements are given below:

• Candidates willing to pursue a PhD in Data Science and related courses must have a master’s degree in related fields like computer science, Statistics, Mathematics, etc
• Some universities have their own entrance exam for PhD level courses
• Marks scored by the candidate in related entrance examinations such as GATE, UGC-NET, CSIR-UGC-NET, etc are also considered for the admission process and these candidates are exempted from giving university entrance exams. But these candidates have to undertake a research skill assessment test. (Only valid for Indian Universities)
• Some colleges also take personal interviews and written tests in shortlisting candidates.
• English test scores of exams like IELTS / TOEFL etc (Only valid for foreign universities)
• Candidates require a set of documents like a 10th Marksheet, 12th Marksheet, Bachelor’s Degree & Marksheets, and Master’s Degree & Marksheet.

Book a FREE session with Leverage Live to ace your English proficiency tests like IELTS, TOEFL, PTE, and more!

When applying abroad it’s always wise to know your options beforehand! Sometimes choosing the right university for you might look like a daunting task.

The following are the top universities in India offering PhD in Data science:

Must Read: How to Write Acknowledgement for Dissertation?

Career Choice after PhD in Data Science

The following are the top career choices after PhD in Data Science:

Researchers conduct their research in an organized and systematic way. They are responsible for communicating their research honestly and ethically. Also, they transfer and exploit their knowledge for the betterment of employees, the environment, and society as a whole and also collaborate with others whenever necessary. 

A data science college professor is expected to design, develop and teach courses in the Data Science domain and related areas. Sometimes, they engage in exploring new methodologies and technologies through research. Also, they mentor and supervise students in their projects and internships too.

A senior data scientist engages in formulating, suggesting, and managing data-driven projects which are in favour of business interests. They also collate and clean data from various entities in order to help their junior data scientists . 

Business analysts help organizations in improving their processes and systems. They conduct research and analysis to solve business problems and introduce solutions to businesses and their clients. 

A machine learning professional is an expert in using data to train models. These models are used to automate processes like image classification, market forecasting, speech recognition etc. 

The average salary in Data Science after doing a PhD can range from Rs 70-75 Lakhs per annum. With more experience, it can be raised to Rs 1 Crore or more. Although it depends on what career path you are choosing and in which state or country you are employed.

Must Read: What is a PhD Stipend?

• Thomson Reuters 

Yes definitely! You can prove to be a leader in the field by doing a PhD in Data Science. And also, a PhD in Data Science also has a higher return on investment as compared to other data science master’s programs.

A PhD in Data Science takes around 4-5 years depending on the university and country you’re pursuing from.

Researcher, college professor, machine learning professional, senior data scientist, and business analyst are some of the positions you can opt for after completing your PhD in Data Science. 

We hope this blog helps you in understanding all the essential aspects of PhD in Data Science. Aiming to study a similar course or thinking of doing a PhD in another field? Sign up for your free 30 minutes of e-counselling with the Leverage Edu team now!

Team Leverage Edu

Leave a Reply Cancel reply

Save my name, email, and website in this browser for the next time I comment.

Contact no. *

Leaving already?

8 Universities with higher ROI than IITs and IIMs

Grab this one-time opportunity to download this ebook

Connect With Us

45,000+ students realised their study abroad dream with us. take the first step today..

Resend OTP in

Need help with?

Study abroad.

UK, Canada, US & More

IELTS, GRE, GMAT & More

Scholarship, Loans & Forex

Country Preference

New Zealand

Which English test are you planning to take?

Which academic test are you planning to take.

Not Sure yet

When are you planning to take the exam?

Already booked my exam slot

Within 2 Months

Want to learn about the test

Which Degree do you wish to pursue?

When do you want to start studying abroad.

September 2024

January 2025

What is your budget to study abroad?

How would you describe this article ?

Please rate this article

We would like to hear more.

Working together, we can reimagine medicine to improve and extend people’s lives.

Principal Scientist with PhenoCycler Fusion experience (PhD)

About the role.

Internal Job Title: Principal Scientist I/II

Position Location: Cambridge, MA, onsite

About the Role:

We are seeking a highly motivated individual passionate about cutting-edge technology to explore single cell multiplex spatial proteomics. This role involves working with the latest generation PhenoCycler Fusion instrument and collaborating with translational immunologists, cancer biologists, and other researchers to advance our understanding of cellular processes in complex tissues and their application to drug development. This role offers exciting opportunities for career development, enhancing leadership skills and influencing collaborative efforts within various disease areas.

Key Responsibilities:

• Operate, maintain, and utilize the PhenoCycler Fusion (formerly CODEX).
• Build and optimize antibody panels.
• Conjugate and perform quality control of reagents.
• Consult with users on potential projects, including sample accessibility and experimental design.
• Optimize procedures, design panels, and provide data analysis consultation.
• Conduct multiplex imaging experiments.
• Perform basic data quality evaluation.
• Analyze data using licensed software.
• Maintain records of procedures and resultant data, both manually and on the computer.

Knowledge, Skills, and Abilities:

• Serve as a leader in spatial proteomic single cell biology and translational research applications, focusing on new targets, biomarkers/patient population selection, and treatment strategies.
• Focus efforts in priority application areas in Biomedical Research (BR) at Novartis to deliver impactful results through matrix collaboration with DA teams.
• Building on success from initial focused efforts, develop broader application strategies at BR in translational and reverse translation research, with support from leaders in Discovery Science, Disease Areas and Biomedical Research.
• Strong interpersonal and communication skills for close collaboration with team members.
• Ability to work effectively in a fast-paced, diverse environment.
• Good judgment, technical problem-solving, and analytical skills.
• Flexibility and adaptability as technology evolves.
• Prior experience in imaging techniques and applications in biological research.
• General lab skills and knowledge of lab safety and infection control.

Qualifications:

• Ph.D. in immunology, biological sciences, biochemistry, or a related field, and 2+ years of related postgraduate work experience
• Other technical and academic degrees will be considered with relevant research experience.
• 3+ years of demonstrated skill and experience using CODEX/PhenoCycler.
• Possess deep knowledge and expertise in immunology, biology, and multi-omics applications in translational research across various disease areas such as oncology (ONC), immuno-oncology (IO), immunity-driven diseases, and related treatment strategies.
• Understanding sample preparation, instrument optimization, and data analysis.
• Interest in bioinformatics and experience with software.
• Ability to identify and troubleshoot critical issues.
• Detail-orientated

Why Novartis: Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture

You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook: https://www.novartis.com/careers/benefits-rewards

Commitment to Diversity and Inclusion / EEO: The Novartis Group of Companies are Equal Opportunity Employers and take pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.

Novartis Compensation and Benefit Summary: The pay range for this position at commencement of employment is expected to be between $112,800 to $186,000/year; however, while salary ranges are effective from 1/1/24 through 12/31/24, fluctuations in the job market may necessitate adjustments to pay ranges during this period. Further, final pay determinations will depend on various factors, including, but not limited to geographical location, experience level, knowledge, skills, and abilities. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network

Commitment to Diversity and Inclusion: Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network

Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers who are focused on building and advancing a culture of inclusion that values and celebrates individual differences, uniqueness, backgrounds and perspectives. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We are committed to fostering a diverse and inclusive workplace that reflects the world around us and connects us to the patients, customers and communities we serve.

Accessibility & Reasonable Accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [email protected] or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.