How to Apply
If you are interested in the program,
feel free to message us directly to receive recruiting updates at
Who Should Apply?
We are seeking highly motivated individuals to join MassMutual as junior data scientists in our Data Science Development Program (DSDP). Qualified applicants have backgrounds in computer science, statistics, mathematics, or related fields and are enthusiastic about pursuing a career in data science. Applicants must have solid quantitative and computational skills and have a working knowledge of languages such as R, SQL, or Python.
We are looking for individuals who are comfortable working in a challenging, fast paced environment and are extremely self-motivated. Data science projects are often complex, therefore we are seeking individuals who are comfortable wrangling with unstructured, difficult problems and are comfortable thinking outside the box and taking initiative. Those who enjoy tackling complex tasks in a collaborative environment are well-suited to a position on our team.
We accept applications from both early career professionals and from graduating seniors with demonstrated work experience. Qualified applicants will demonstrate the following:
- Academic study or independent training in computational, quantitative, or technical fields, such as computer science or statistics
- Research and/or practical experience in related fields
- Technical expertise
- Demonstrated work experience through part time employment, internships, or professional endeavors
- Leadership and community involvement
- Strong communication skills as demonstrated through personal statement
- Supporting references
To supplement learning and development, members of the DSDP spend up to 3 years taking graduate-level courses at UMass Amherst in Computer Science
and Statistics while working full time, and many pursue a part-time graduate degree. Only those up to the task of balancing rigorous coursework with challenging project work should apply. Additionally, if you've
already completed a graduate degree program in a related field,
the first-year development position is probably not right for you and we encourage you to check out our other career opportunities.
- 1st Round Applications accepted Sept 1 - Oct 15, 2017
- 1st Round Decisions by end of November, 2017
- 2nd Round Applications accepted Jan 1 to Feb 28, 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:
Resume: Please submit your most updated resume; one page maximum.
Personal statement: A maximum one-page document describing
your qualifications and ability to contribute to an engaging
data science team. Please include information about how you became interested in the field of data science as well as why you would like to pursue a career at MassMutual.
Academics: An official or unofficial transcript or other details of your academic background or training.
Research and practical experience: Up to three examples that provide information about your 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: Up to three examples of 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)
- Relevant class projects
Summary Sheet: Every portfolio submission should include a 1 to 3 page summary document
that includes the following sections and information:
- Personal Info: Name, School, Major, Phone Number, Email Address
- Relevant classes: List only your courses (and corresponding grades) which are most relevant to data science work
- Work experience: List up to four bullet points of past or current employment and work experience
- Leadership and Community Involvement: List up to four bullet points of leadership experience and community involvement
- Portfolio summary: List each project or data science example you've included in your portfolio (to demonstrate research, practical, or technical expertise) and a 1-2 sentence summary of each and what you learned from that project.
- References: At least two (2) references are required, and should be listed at the end of the Summary Sheet. Please provide name, title, contact information, industry/company, and relationship for each reference. At least one reference must be a faculty member, and at least one must be a manager, employer, or industry partner. References should be able to speak to your self-motivation, persistence, and leadership, ad your potential to work in a fast-paced environment on a collaborative team.
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.
Those who submit portfolios will also need to complete a brief application form through MassMutual's employment portal to complete their application. Check back here in early October for that link.
Interviews: Fall Interviews will take place October 24 - Sept 6.