Application Process

We're recruiting now our next development class!

How to Apply

If you are graduating in 2018 and interested in the program, fill out our initial interest form or feel free to message us directly to receive recruiting updates at

Who Should Apply?

Members of the DSDP spend 3 years taking graduate-level courses offered at UMass Amherst in Computer Science and Statistics. This aspect of our program is just as critical as the full-time project-based work for MassMutual because our goal is for you to develop into a fundamentally trained, well-rounded, and experienced data scientist. If you've already completed a graduate-degree program with similar coursework, the first-year development position is probably not right for you. But, if you're a motivated individual with a solid quantitative and computational background, please join us!

Information Sessions at Amherst Location

  • Mid-September, 2017 (Time and Day TBD)
  • Late-February, 2018 (Time and Day TBD)


  • 1st Round Applications accepted Sept 1 - Oct 30, 2017
  • 1st Round Decisions by end of November, 2017
  • 2nd Round Applications accepted Jan 1 to Feb 30, 2018
  • 2nd Round Decisions by late March 2018
  • Full-time positions will start June 4, 2018

Application Process

We are accepting application portfolios starting on September 1, 2017. The portfolio should include the following:

  • Personal statement: A one-page document describing your qualifications and ability to contribute to an engaging data science team.
  • Academics: Details of your formal academic background or training with a college transcript for all completed/anticipated degrees.
  • Research and practical experience: Relevant documents and information that give us data points with respect to your prior research and practical experience in the realm of data science. Some examples include:
    • Peer-reviewed articles in relevant disciplines
    • Posters at relevant conferences, workshops, or colloquia
    • Class project reports in relevant courses
    • Non-peer-reviewed technical reports or memos
    • Evidence of datafest or similar event participation or awards
  • Technical expertise: Evidence of technical proficiency that could form the basis of fundamental data science skills. Some examples include:
    • Relevant code snippets (that may support your prior research or projects)
    • The URL to your Kaggle profile, Github account with code repositories, or Stackoverflow or similar website profile
    • URLs of websites you own or have maintained
    • Evidence of open-source contributions (e.g. Google Summer of Code)
  • Recommendations: Two (2) letters of recommendation from faculty, industry partners, or others that can provide insight on your academic background, propensity to become a data scientist, or intangible attributes that would indicate your potential success as a member of the DSDP. These letters must be sent directly by those writing the letters as a PDF to the DSDP recruiting email address (

Submission instructions: Send a .zip file called <firstname>_<lastname> to Please ensure that your portfolio is no larger than 10MB. We won't be running any of your code, so there's no need to include data sets.