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
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
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
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
- 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
Submission instructions: Send a .zip file called
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.