The Los Alamos National Laboratory Community Data Science Fellow is a paid, full-time, 10-week summer internship that provides a unique opportunity for a student to gain hands-on experience with scientific project leadership as well as data science.
The LANL Community Data Sprint, now in its sixth year, partners local Northern New Mexico organizations with LANL data scientists and machine learning researchers, using data collected by those organizations to understand community issues and provide actionable insights. The effort culminates in a data sprint where a group of LANL staff and students devotes a full week of time collaborating closely to rapidly produce the data-related insights requested by the partner organizations. Community organizations for 2026 have not yet been selected. News articles highlighting our past sprints are available:
The selected Community Data Science Fellow will work closely with and receive one-on-one mentoring from the Community Data Sprint organizing team, and be involved with all aspects of the Community Data Sprint. This will include helping with organizing and planning before the data sprint week, interfacing with community partners, assisting with dataset transfer and wrangling, participating in the sprint week itself both as a data scientist and as a facilitator, and assisting with follow-up activities such as producing final reports and evaluating impact.
Position Duration: 10 weeks, approximately early June to mid-August
Note: This position is in-person at Los Alamos National Laboratory.
The Community Data Science Fellow is a unique, interdisciplinary position. This position is best suited for upper-level undergraduate or graduate students in either a data science related-field (e.g., computer science, engineering, statistics, mathematics), or in a project management-related field (e.g., public policy, communications, business, nonprofit management). Ideal candidates will have experience in both data science and project leadership, as well as exceptional written and verbal communication skills, particularly with regard to communicating technical results to a non-technical audience. United States citizenship is not required. To be considered for the position, students should have and maintain a 3.0 GPA for undergraduate students or 3.2 for graduate students, on a 4-point scale.
In addition to the questions below, you will be asked to send your resume/CV, a cover letter, and your academic transcripts. Unofficial university transcripts will suffice for the initial stage of the application process. If offered a position, official transcripts will be requested. We recommend that you prepare your supplemental documents prior to beginning the application.
Please prepare a cover letter that specifically addresses the following:
please use this form and submit an application to either IRC139805 - Undergraduate and Graduating HS Senior Internship - Computational Sciences or IRC139784 -Graduate Internship - Computational Sciences at lanl.jobs.
Competitive candidates will be contacted for interviews by mid February 2026, with a final selection announced shortly after. The accepted student will be required to undergo a background check and drug test as part of the hiring process to access Laboratory property.
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