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Master’s in Data Science Salary

Introduction

Data science master’s programs are a relatively new phenomenon, with most launching in the last five to seven years. These programs have gained ground on traditional master’s in statistics or computer science, which many data scientists pursued prior to full data science programs being offered.

No matter what subject you study, one thing remains true: A master’s degree results in a significant salary bump. We took a closer look at master’s in data science salaries and found:

  • The average data science master’s salary after graduation is $126,830
  • For entry-level positions, a master’s degree resulted in around a $5,000 salary increase
  • For mid-career positions, a master’s degree resulted in around a $13,000 salary increase

In short, a master’s degree, although not necessary to pursue a data science career, can significantly increase career earnings. We took a closer look to compare data science bachelor’s vs master’s salaries and provided some information about weighing pros and cons.

**See the most up-to-date earnings on our Data Scientist Salaries page. **

Data Science Master’s vs Bachelor’s Salary

At all career levels, a master’s degree results in a salary increase. Yet, the wage gap increases significantly from entry-level to mid-career data scientists. Here’s a look at bachelor’s vs master’s in data science salaries:

Another option is a PhD. For example, a PhD in Economics, a PhD in Data Science, or a PhD in Statistics all provide training for data science research jobs with high starting salaries.

Data Science Master’s Salary: By Title

  • Data Scientist - Many enter the field as data science generalists, usually at the IC-II level. Data scientists are responsible for building models, data pre-processing, and data validation

  • Data Architect - Data architects are responsible for designing data infrastructure, and sometimes building it as well. Architects typically collaborate closely with data engineers.

  • Machine Learning Engineer - Some data science master’s programs offer specializations in machine learning, deep learning, and AI. These programs help prepare graduates for specialized ML roles, like engineer, scientist, or AI specialist.

  • Data Science Manager - Although a master’s program isn’t specifically designed to prepare you for management, a master’s is often a required credential for the job. If you have prior management experience, you could potentially graduate and land a manager position. Data science manager salaries are some of the highest in the industry.

Is a Master’s in Science Worth It?

One question we hear a lot is: Do I need a master’s for data science? The short answer is that if you are planning on pursuing a career in data science, you don’t necessarily need a master’s. It’s also important to note that it’s not a golden ticket to a data science job.

Rather, a master’s is a good investment if:

  • You are making a big career change (e.g. switching from finance to data science)
  • You have the time to study and the resources
  • You want to master DS concepts

The big consideration is cost. In-person master’s programs cost an average of $45,000, and require 1-3 years of study. Even online programs run an average of $30,000. If you have the time and resources to invest, a graduate degree is an effective tool for helping you advance in your career. Plus, along with the salary increase, graduate programs also offer benefits like:

1. Domain Expertise - You’ll be able to dive deep into foundational data science concepts, like statistics, machine learning, and probability. Plus, most programs allow you to specialize and gain experience in advanced subjects like NLP, text mining, deep learning, or computer vision.

2. Portfolio Work - Most data science master’s programs encourage project-based learning, competing in Kaggle competitions, and developing a data science portfolio. This can be a powerful tool for helping you land a competitive job.

3. Networking - The best data science master’s programs have established career networks and can help connect you with alumni working in the field. These references can help to fast-track you into landing interviews.

Data Science Master’s: Pros and Cons

Should you get a master’s in data science? Our founder Jay took a closer look in the video below, and he answered questions you might have about the reasons why to pursue a data science master’s.

Specifically, a master’s is a good idea if you are considering a dramatic career switch, if you want to learn the fundamentals of data science, or if you’re a good student and prefer structured learning.

Yet, there are pros and cons to pursuing a degree, and a master’s doesn’t guarantee you actually land a job. Check out the video for more more specifics. It can help you understand if a master’s program is right for you:

More Data Science Learning Resources

A data science master’s degree will certainly impact your career earnings. However, although a master’s degree is becoming an increasingly required qualification (or preferred qualification, at a minimum) for many DS jobs, you must still have:

  • A strong portfolio
  • Good references
  • A variety of experiences

Master’s programs can help you to build your portfolio and professional network, and many programs also offer career counseling to help you land jobs. Ultimately, it comes down to your ability to ace the interview.

Check out these resources from Interview Query to brush up on your data science skills and see the most common interview questions: Data Science Course, Machine Learning Course, 500+ Data science interview questions.