Data Science Institute

Career Outcomes

Discover what our graduates do after completing the Data Science Master’s Program, where they are employed, and how we estimate our post-graduation employment rates.

The Data Collection Process

Every data science project begins with data collection, and real-world data is often quite messy. It’s crucial to understand exactly how the data is gathered and what assumptions are made in the estimates to properly interpret the insights.

After students graduate from the program, we collect their LinkedIn profiles. These profiles help us estimate post-graduation employment rates, track the industries our alumni work in, the companies they join, and their current job titles. We review everyone’s LinkedIn profile once a year, usually in August, to gather this data. As you can imagine, there are a few challenges with this process:

  • While most students create a LinkedIn profile, a few do not.
  • Not everyone keeps their profiles up-to-date. Sometimes, we hear the great news that an alumni has landed a job, but their LinkedIn profile doesn’t reflect this.

Insights

We categorize alumni into three groups to estimate employment rates:

  • ne: The number of alumni who are employed (the "e" in ne stands for "employed").
  • no: The number of alumni who display the "Open to work" badge on their profiles, indicating they are actively seeking jobs (the "o" in no stands for "open to work").
  • nu: The number of alumni who either don’t have a LinkedIn profile or whose profiles haven’t been updated since graduation (the "u" in nu stands for "unknown").

We calculate lower and upper estimates of post-graduation employment rates based on the assumption that profile information is current, though this may not be true for everyone.

The employment rate 2-3 months after graduation is around 50% to 80%. For the 2022 cohort, which had 40 graduates (most in May 2024, with some in January 2024), the values are ne = 20, no = 8, and nu = 12 as of August 2024. The lower estimate is that 50% of our alumni are employed 2-3 months after graduation, assuming none of the alumni in n_u are employed (ne/(ne+no+nu)). The upper estimate is 80%, assuming all alumni in nu are employed ((ne+nu)/(ne+no+nu)).

The employment rate a year after graduation is around 80% to 90%. For the 2021 cohort, which had 46 graduates (most in May 2023, with some in January 2023), the values are ne = 38, no = 3, and nu = 5 as of August 2024. Based on these numbers, the lower and upper estimates of the employment rate are 82% and 93%, respectively, following the same calculation as above.

Please keep in mind that these figures are estimates based on the assumption that everyone’s LinkedIn profile is accurate and up-to-date, which may not be the case for all. Data science can indeed be quite messy!

Industries

Since the first cohort enrolled in 2017, 235 students have completed our master’s program, and we have employment information on 181 alumni. Approximately 75% of our alumni work in finance, tech, health, or pursue a PhD after graduation ("grad"). The doughnut chart below illustrates the industry breakdown.

Example Placements

Learn a bit about the employment and further education of our alumni! These lists are not exhaustive but are illustrative of DSI alumni careers.

A partial list of companies that employ our alumni:

  • Accenture
  • Aetna
  • Allen Institute for AI
  • Amazon
  • Bank of America
  • Bayer
  • Biogen
  • BlackRock
  • Broad Institute of MIT & Harvard
  • ByteDance / TikTok
  • Capital One
  • Citi Bank
  • Citizens Bank
  • Comcast
  • CVS
  • Dyno Therapeutics
  • Eli Lilly & Company
  • EY-Parthenon
  • Food & Drug Administration
  • FM Global
  • General Motors
  • GoHealth
  • Goldman Sachs
  • Google
  • GSK
  • Hasbro
  • HelloFresh
  • IBM
  • Instacart
  • Intuitive
  • iRobot
  • JPMorgan Chase
  • Liberty Mutual Insurance
  • LinkedIn
  • Los Alamos National Laboratory
  • Luma Health
  • Mass General Hospital
  • McKinsey & Company
  • Meta
  • Microsoft
  • Oracle
  • Pandemic Response Lab NYC
  • PayPal
  • Peleton
  • Philips
  • Rocket Central
  • Skims
  • Sony Entertainment
  • Square
  • State Farm
  • Strava
  • Swiss Re
  • Synchrony
  • Tesla
  • Verizon
  • Visa
  • Wayfair
  • Wellframe
  • Zest AI

We have multiple alumni working at bolded companies.

A partial list of positions our alumni have received:

  • AI Engineer
  • Applied Scientist
  • Assistant Director of Data Science
  • Bioinformatician
  • Business Intelligence Engineer
  • Clinical Data Manager
  • Computational Biologist
  • Consultant
  • Data Engineer
  • Data Scientist
  • Director of Global Corporate & Investment Banking
  • Engineering Manager
  • Financial Analyst
  • Global Business Analyst
  • Growth Analyst
  • Health Data Scientist
  • Founder
  • Investment Banking Analyst
  • Law Student
  • Lead Program Manager
  • Machine Learning Engineer
  • MBA Candidate
  • Natural Language Processing Engineer
  • PhD Student
  • Policy & Planning Staff
  • Postdoctoral Research Associate
  • Principal Data Scientist
  • Product Marketing Manager
  • Quantitative Research Analyst
  • Research & Development Engineer
  • Risk Analyst
  • Scientific Investigator
  • Software Engineer
  • Technical Product Manager
  • Venture Capital Scout

 

Many of our Data Science Masters alumni choose to pursue their doctorate degree. Alumni have pursued PhDs in a variety of fields including Astrophysics, Biology, Biomedical Informatics, Chemical Engineering, Chemistry, Computer Science, Engineering, Molecular Biology, Neuroscience, Philosophy, Physics, Political Science, Sociology, and Statistics. Other alumni have also pursued MBA degrees and JD degrees. Students have studied at a myriad of institutions such as Boston University, Brown University, MIT, Oxford University, Stanford University, Stony Brook University, UC Santa Cruz, University of Georgia, UPenn, and Vanderbilt University. 

Many alumni who have pursued advanced degrees have gone on to achieve Postdoctoral Research Associate positions at institutions such as Brown University, Yale University, University of Regensberg, Northeastern University, and Harvard University.