Data Science Research Opportunities for High School Students
Updated: Sep 9
Updated September 2, 2026
TL;DR
Eleven programs on this list put high schoolers into real data science research projects, not just coding classes. Only one, the Lumiere Research Scholar Program, is fully remote and open to students worldwide; every other program is limited to a specific city, state, or US citizens, so check the location and eligibility lines before you get attached to a program. Costs vary widely: NIST's SHIP and Johns Hopkins' ASPIRE are unpaid and cost nothing to join, several others pay a real stipend, and George Mason's ASSIP now charges $1,299 in tuition (fully waived for students with financial need). Programs run anywhere from two weeks (Stanford's AIMI internship) to a full year (Lumiere), and a couple, including Stony Brook's Simons program, require your school to nominate you before you can even apply. If none of the geography-restricted programs fit you, or you want a project you fully own instead of a shared lab placement, look at the Lumiere Research Scholar Program. It pairs you 1-on-1 with a PhD mentor on an independent project, with full financial aid available.
If you're a high schooler interested in data science, you probably already know how competitive the space is. One way to get ahead is to build a real skill set early, not just take a class, and that's where the choice between these programs matters. You can pick between hands-on lab technique (strongest at UChicago's DSI Summer Lab or George Mason's ASSIP), a federal research environment (NIST, NLM), or a written project you can describe in an application essay (Lumiere). A student who spent a summer cleaning a real dataset and building something with it reads very differently on an application than one who sat through lectures, so matching the program to what you actually want to show matters more than chasing the most familiar name.
Why should you do data science research?
Here’s something a lot of resources online won’t tell you - you don’t need to target a career in data science to do data science research. It is a useful skill across all fields!
The same techniques you'd use to study climate data apply just as well to public health, sports, or economics, so a data science project doesn't lock you into one career path the way some other research areas can.
A few concrete reasons to consider it, beyond just "it looks good":
The skills are in demand and outlast any one program. Cleaning a real dataset, building a model, and explaining what it means are skills colleges and employers both value, no matter what you end up majoring in.
It rewards curiosity over memorization. Most high school science classes test what you've memorized. A data science research project tests whether you can ask a good question and go find the answer yourself, which is different work, and often more enjoyable.
It gives you a real story for your application. A named mentor who watched you work for weeks can write a far more specific college recommendation letter than a teacher who only saw your test scores, and a finished project (a poster, an abstract, or a paper) gives you something concrete to describe in an essay instead of a generic "I learned Python" line.
Across recent cohorts of the Lumiere Research Scholar Program specifically, roughly 492 scholars have gone through the program, and completing the independent research project has been associated with an admission rate to selective colleges around 4x the typical applicant baseline. That figure reflects Lumiere's own cohorts, not a guarantee tied to every program on this list, but it's a real, verified number. For more on how admissions officers actually weigh this kind of experience, see our guides to the best summer research programs for high school students and online research mentorship programs.
Data science research topic ideas
Not sure what you'd actually study once you're in a program? Data science is really a set of tools (statistics, programming, visualization) applied to someone else's question, so a project can go in almost any direction. A few areas past students have explored:
Health and biostatistics. Studying the relationship between sleep and activity levels, or looking for patterns in public health data across regions.
Sports and performance analytics. Using play-by-play or player-tracking data to test a specific strategy question.
Climate and environmental data. Analyzing satellite or sensor data to track a specific environmental change over time, the same kind of work NIST and the NASA-affiliated program on this list do.
Social and economic data. Looking for patterns in survey, spending, or demographic data to answer a specific social science question.
This is just a sample. Our full guide to data science research topics for high school students breaks out more than 20 project ideas by subfield, and it's a good next stop once you've picked a program from the list below.
How to get into a data science research program
Get some coding under your belt first. Programs like UChicago's DSI Summer Lab and Stanford's AIMI internship assume basic Python. A free online course, or your school's intro computer science class, is usually enough to look ready.
Write a specific personal statement, not a polished, generic one. NIST's SHIP, Johns Hopkins' ASPIRE, and George Mason's ASSIP all weigh essays heavily, since none of them require a transcript, and ASSIP doesn't even ask for a GPA. A clear, honest paragraph about why you want to do this kind of work beats an impressive-sounding one.
Ask your school about nomination-only programs early. Stony Brook's Simons Summer Research Program requires your school to nominate you, with a limit of two students per school, weeks before the general deadline. Talk to a science teacher or counselor in the fall, not the spring.
Apply locally and nationally at the same time, if you can. If you live near Chicago, Seattle, or the DC-Baltimore-Northern Virginia area, apply to the local pathway program (Digital Scholars, Spark SMP, or ASPIRE) alongside a national option. Your odds are almost always better for a program tied to your own region.
If your age, grade, or location rules out every campus program, look at remote mentorship instead. A track like the Lumiere Research Scholar Program doesn't carry the geographic or grade restrictions that campus labs do, so it's worth applying to no matter where you live or what grade you're in.
Remote and virtual-friendly programs. These three are the only programs on this list that don't require you to live near, or travel to, a specific campus.
1. Lumiere Research Scholar Program: Data Science Track
Application deadline: Rolling, with spring, summer, fall, and winter cohorts
Duration: 12 weeks to 1 year
Location: Fully remote, open worldwide
Eligibility: Currently enrolled in high school, with strong academic achievement
Cost: Tuition-based; full financial aid available
Acceptance rate: Selective; roughly 4,000 applicants for about 500 spots across all subjects
The Lumiere Research Scholar Program pairs you with a PhD mentor for 1-on-1 work on an independent data science research project, ending in a university-level research paper.
Because the mentorship is individual rather than shared with a lab group, you define the project. Past students have explored topics like machine learning applications, natural language processing, and data visualization for public health.
Who it's right for: Students outside the US, students in cities without a research university nearby, and anyone who wants a written research output rather than a shared lab placement. It's also the realistic option if you're a freshman or sophomore, since most campus programs on this list won't take you yet. See the application details here.
Application deadline: Late February (extended by a day most years; check the current cycle)
Duration: 2 weeks, offered across two summer sessions
Location: Fully virtual
Eligibility: Students entering grades 9 to 12 in the fall, at least 14 by the program's start, currently attending a US high school. International students and students living outside the US cannot apply.
Cost: The program has moved from a free model to a paid, subsidized one as it has grown. Program fees are due on acceptance and are non-refundable, though fee waivers are available for demonstrated need. Confirm the current fee on AIMI's own page before applying, since it has changed more than once in recent years.
Stanford's Center for Artificial Intelligence in Medicine and Imaging runs this short, virtual internship introducing high schoolers to how AI is used in healthcare. You'll work on a practical AI project in a small group, attend technical lectures, and hear from guest speakers through Career Lunch and Learn sessions. Strong projects may go on to a scientific conference abstract with a Stanford mentor's help. Our full guide to the AIMI program has more on past projects and what the application process looks like.
Who it's right for: Students who want a first, low-commitment look at applied data science and AI before committing to a longer program, and students specifically interested in the intersection of data science and medicine. Be aware this is shorter and more structured than the mentorship programs on this list; you'll finish with a group project, not an independent paper.
Application deadline: Rolling; seats are first-come, first-served, and the cohort is capped at 50 students
Duration: Runs through the summer into late August, including a five-week research and paper-writing period
Location: Hybrid, mostly virtual, with optional in-person sessions at George Mason's Fairfax, VA campus
Eligibility: Open to all high school students
Cost: Contact the program directly (execed@gmu.edu) for the current fee structure; need-based scholarships are available
Students analyze real NASA mission data, including observations from the TESS and James Webb Space Telescope missions, and write a professional-style research paper under George Mason faculty guidance. It includes group virtual telescope sessions and ends with a research paper that's published on George Mason's Young Scholars Journals page, plus an optional presentation at a research conference on campus.
Who it's right for: Students anywhere in the country who want a genuine data-analysis research paper without needing to travel, and students specifically drawn to astronomy or space data over general computer science. The 50-student cap means it's worth applying early in the cycle rather than waiting.
University and federal lab research placements. These five put you inside an actual university lab or federal research agency, working alongside scientists on their own projects.
Application deadline: Mid-January
Duration: 8 weeks, mid-June to early August
Location: University of Chicago, Hyde Park campus, Chicago, IL
Eligibility: Any current high schooler (freshman through senior) who lives in and attends school in the Chicago area. Students from outside Chicago cannot apply, even if they plan to attend college there. International students need to provide documentation of US work authorization.
Cost: Free to participate, plus a $4,800 stipend. Housing is not provided for high school participants.
The Data Science Institute Summer Lab is a paid research program pairing you with a mentor across fields like computer science, public policy, climate and energy policy, and biomedical research. As a research assistant, you'll build skills in research methods and teamwork while working on a real applied data science project, then present your work at an end-of-summer symposium. Read our full review of the program to learn more about what past cohorts worked on.
Who it's right for: Any Chicago-area high schooler, not just seniors. This is one of the better-paid options on this list, so it's worth applying to even if data science is just one of a few interests you're weighing.
Application deadline: Late January
Duration: 7 weeks, late June to early August
Location: NIST laboratories in Gaithersburg, MD, or Boulder, CO
Eligibility: Current high school juniors, seniors, or recent graduates who are US citizens with a minimum unweighted GPA of 3.0. You must have a permanent residence within 50 miles of your host campus, or arrange and pay for your own housing and transportation; there are no exceptions to the residency rule.
Cost: Free; this is an unpaid internship with no stipend.
NIST's Summer High School Intern Program, known as SHIP, places you directly in a working federal research lab. In the Information Technology Laboratory, past projects have covered data mining, machine learning, computer network modeling, and information visualization. You'll work full-time alongside NIST scientists for the full seven weeks and present a research poster at the end.
Who it's right for: Students who genuinely live near Gaithersburg or Boulder, or who can arrange their own housing there for the summer. The 50-mile residency rule is strict and unwaived, so confirm your distance from either campus before you invest time in the application.
Application deadline: Rolling review starting in mid-January, closing in late February
Duration: 8 to 12 weeks, starting in June, with flexible start dates
Location: National Library of Medicine, NIH campus, Bethesda, MD
Eligibility: US citizens or permanent residents who are at least 18 by June 1 (or 17, if your permanent address is within 40 miles of an NIH campus). You must be enrolled at least half-time as a high school senior, or already accepted into a college program starting in the fall, and have completed relevant coursework in computer science, data science, informatics, or math. A GPA of 3.0 or higher is preferred, though a lower GPA can be addressed in your personal statement.
Cost: Free, plus a stipend based on the NIH Intramural Research Training Award scale, which is updated annually.
DSI Scholars work full-time on computational research projects that apply data science methods, like machine learning and statistical modeling, to biology and health questions. Recent cohorts have included high schoolers working alongside undergraduates, graduate students, and even medical students. The program includes seminars and professional development sessions and ends with a poster presentation at NLM's Summer Poster Day.
Who it's right for: Students interested specifically in health and biomedical data, since every project here applies data science to a biological or clinical question rather than a general topic. The 17-if-nearby exception matters if you're a younger student who lives close to Bethesda.
Application deadline: Early February; your school must nominate you by late January, before the general application even opens to you
Duration: About 6 weeks, late June to early August
Location: Stony Brook University, Stony Brook, NY. Remote participation isn't available; you need to live on campus or commute for the full program.
Eligibility: You must be a current high school junior (11th grade) at the time you apply, a US citizen or permanent resident, and at least 16 by the program's start. Each high school can nominate a maximum of two students, so ask your science department about the nomination process well before the deadline.
Cost: Free, funded by the Simons Foundation, plus a stipend awarded at the closing symposium. You're responsible for your own housing if you choose to commute rather than live on campus.
The Simons Summer Research Program matches you with a Stony Brook faculty mentor and a research group for hands-on STEM research, including projects in applied math, machine learning, and high-performance computing. You'll attend weekly faculty talks, take part in workshops, and finish with a written research abstract and a poster. See our 7 reasons to apply to Simons for more on the nomination process and what past mentors have worked on.
Who it's right for: Current juniors whose school is willing to nominate them well ahead of the deadline. This is one of the most selective programs on this list, and the nomination requirement alone rules out students at schools without an established Simons pipeline, so start the school-side conversation early if you're interested.
Application deadline: Mid-February
Duration: 8 weeks, mid-June to mid-August
Location: Remote, hybrid, and in-person formats are all available, based at George Mason's Fairfax and Manassas, VA campuses for in-person and hybrid placements. Remote placements are open to students anywhere.
Eligibility: Remote and computer-lab interns must be at least 15 by the program's start; in-person or hybrid "wet lab" placements (involving chemicals or biohazards) require you to be at least 16. There's no maximum age, and no citizenship requirement is listed. No transcript, GPA, or letter of recommendation is required to apply; admission is based on your essays and a shortlist of preferred mentors.
Cost: $1,299 in George Mason tuition for 3 college credits, plus a $25 application fee. Both are fully waived for students who qualify for free or reduced lunch, or Pell Grant assistance.
ASSIP pairs you with a George Mason faculty researcher across areas including machine learning, data engineering, and computational research, working roughly 30 hours a week for the full eight weeks. You'll use real lab equipment and technologies where relevant, and the program concludes with a research symposium where you present your findings. Successful completion earns 3 college credits. Our deep dive on whether ASSIP is worth it covers the mentor list and past projects in more detail.
Who it's right for: Students who want the strongest hands-on research experience on this list and don't mind paying for it, since the tuition covers real college credit rather than just a certificate. If cost is a barrier, the fee waiver makes it accessible for students with financial need, so check your eligibility before ruling it out. Note this is a real cost change from what this program used to charge, so confirm current pricing on George Mason's site before applying.
City- and region-specific pathway programs. These three are tied to a specific metro area, but they're worth knowing about if you live nearby.
Application deadline: Applications typically open in February and close in early May
Duration: 6 weeks, late June to late July
Location: Discovery Partners Institute, Chicago, IL, in partnership with the University of Illinois Chicago and Urbana-Champaign
Eligibility: Rising 11th and 12th graders, plus first-year college students at City Colleges of Chicago and Illinois institutions
Cost: Free; public transit passes are provided for students with financial need
The Digital Scholars Program aims to build a more diverse pipeline into tech careers, with priority for Black, Latinx, and first-generation students. In the Data Science Discovery track, you'll work with real-world datasets in Python, building skills in data analysis, visualization, and statistical modeling, alongside workshops on AI, machine learning, and entrepreneurship led by professionals from Chicago's tech community.
Who it's right for: Chicago and Illinois students who want a structured, no-cost introduction to data science with a strong mentorship and networking component, especially students from backgrounds underrepresented in tech.
Application deadline: Applications typically open in March or April and close in May
Duration: 8 to 12 weeks, typically May to August; timelines vary by project
Location: Primarily the Greater Seattle, WA area, with virtual and in-person projects both available
Eligibility: High school students who are US citizens or permanent residents and live in the United States, generally in the Seattle area
Cost: Free; some individual projects offer a stipend, though not all do
Spark SMP matches you with a mentor from industry, academia, or the local community on a real project. Data science-focused projects have included applying machine learning and statistical methods to real datasets, alongside broader tracks in engineering, biotechnology, and technical writing. The program is volunteer-run and highly selective. Our tips for landing a Spark SMP internship go deeper on how the matching process actually works.
Who it's right for: Seattle-area students who want one-on-one mentorship from a working professional rather than a university lab placement, and who are comfortable with a program where project offerings change from year to year.
Application deadline: Applications open January 1 each year; this is the only application window for the full year, including any academic-year continuation
Duration: About 9 weeks over the summer, from a required late-June orientation through late August. Students in good standing may continue into the academic year with their mentor's agreement, without a separate application.
Location: In person at the Johns Hopkins Applied Physics Laboratory in Laurel, MD, or virtually, depending on your mentor's project
Eligibility: High school juniors and seniors with a GPA of 2.8 or higher, who are US citizens (green card holders are not eligible) and permanent residents of specific counties in Maryland, a handful of Northern Virginia counties, or Washington, DC. Full details are on APL's eligibility page.
Cost: Free to participate; this is an unpaid internship with no stipend.
ASPIRE pairs you with an Applied Physics Laboratory staff mentor for a hands-on project in an area like data analysis, artificial intelligence, or programming, and you work 30 to 40 hours a week. It's highly competitive: roughly 7% of applicants are accepted. Virtual participants don't need their own transportation, though in-person visits do, since APL isn't reachable by public transit. See our 8 reasons to apply to ASPIRE for more on the placement areas and timeline.
Who it's right for: Students who genuinely live in APL's eligible counties and can commit to a demanding weekly schedule. The strict US citizenship and county-residency rules mean it's worth double-checking your eligibility on the official page before applying, since permanent residency in a nearby state isn't enough.
Frequently asked questions: data science research programs for high school students
Are data science research programs for high school students free, or do they cost money?
It's a mix. NIST's SHIP, Johns Hopkins' ASPIRE, and Stony Brook's Simons program cost nothing and don't require any payment. UChicago's DSI Summer Lab and NLM's DSI Scholars Program are free and pay you a stipend. George Mason's ASSIP now charges $1,299 in tuition plus a $25 fee, though both are waived for students with financial need, and Stanford's AIMI internship charges a program fee that has increased as the program has grown. The Lumiere Research Scholar Program is tuition-based with full financial aid available.
Can freshmen or sophomores do data science research?
Most campus programs on this list are restricted to juniors and seniors. The Lumiere Research Scholar Program and George Mason's NASA Data Science Research Program are open to any grade, and George Mason's ASSIP will take remote or computer-lab interns as young as 15. Beyond those, a freshman or sophomore's best options are usually remote mentorship programs rather than campus labs.
Are any of these programs open to international students?
Only the Lumiere Research Scholar Program is fully remote and open to students worldwide. NIST's SHIP, NLM's DSI Scholars Program, Stony Brook's Simons program, and ASPIRE all require US citizenship or, at most, permanent residency in a specific area. Stanford's AIMI internship and UChicago's DSI Summer Lab are both restricted to students who attend a US high school (and, for UChicago, live in the Chicago area specifically).
What's the difference between a data science research program and a data science internship or summer program?
The programs on this list all end with a specific research output, a paper, a poster, or a written abstract, produced under a named mentor. A general internship may focus more on skill-building or shadowing without a defined research question, and a summer program can be closer to a structured course. If you specifically want a paid internship, our guide to data science internships for high school students covers that format instead.
How competitive are these programs?
It varies widely. ASPIRE accepts about 7% of applicants, and Stony Brook's Simons program and Lumiere's Research Scholar Program are both selective. Others, like George Mason's ASSIP and NASA Data Science Research Program, are more accessible if you meet the basic eligibility bar, since they weigh essays and fit over test scores or GPA.
Do I need to already know how to code before applying?
Not for most of these programs, but it helps. Programs like UChicago's DSI Summer Lab and Stanford's AIMI internship assume some basic Python, so a free online intro course or your school's computer science class beforehand can make your application, and your first weeks in the program, much smoother.
When should I start applying?
Deadlines cluster from mid-January through late February for summer programs, with a few, like Discovery Partners Institute's Digital Scholars Program, staying open into April or May. Stony Brook's Simons program is the exception that requires the earliest action: your school needs to nominate you by late January, before you can submit anything yourself. The Lumiere Research Scholar Program runs rolling cohorts year-round, so it doesn't follow this calendar.
More from the Lumiere blog
If you’re looking for more such opportunities, or you want to dig into a specific program in data science more, these guides go deeper:
Data science internships for high school students, for paid placements that skip the independent research paper
Data science summer programs for high school students, for structured, coursework-style programs
Data science competitions for high school students, if you want to compete rather than intern
Data science research topics for high school students, for more than 20 project ideas once you've picked a program
Free research mentorship programs for high school students, for no-cost options beyond this list
Online research mentorship programs for high school students, for more fully remote options like Lumiere's
The best summer research programs for high school students, for a broader view across every subject, not just data science
Stephen Turban is the co-founder of Lumiere Education and a graduate of Harvard College, where he earned an A.B. in Statistics before beginning a PhD at Harvard Business School. A former McKinsey & Company consultant and former researcher, his research has been covered by the Harvard Business Review, The Economist, BBC News, Freakonomics Radio, and the Washington Post. In his articles for Forbes, he writes on what students and professionals can learn from high school research, high school passion projects, critical thinking, and mentorship. At Lumiere, he leads a selective research program where students work one-on-one with a research mentor to develop an independent research paper. Connect with him on LinkedIn.