Empowering Youth inData Science Education
We engage middle school, high school, and community college students in the exciting world of big data and data fluency — preparing them to thrive in a data-driven society.
Get Involved
Whether you're here to compete, teach, mentor, judge, or sponsor — there's a spot for you.
What Is The DataJam?
A minute-long look at our programs, timeline, and community — straight from the site you're on right now.
Our Impact
Building a stronger data community through education, mentorship, and collaboration
What They're Saying
Analyzing data shows you new insights and reveals patterns in the world that are exciting to learn about.
It's very good to work with a team because you can encourage each other and you can learn from each other.
Your students will be dragging you back into it the next year. They've just heard about it from other students and they want to get involved.
"I discovered my love for data science in my first year of college and never looked back. Being able to share that excitement with students through DataJam is exactly what I was looking for."
"I study how people think and how data shapes our world. Mentoring students who are just beginning to see those connections for the first time is endlessly rewarding."
"My path to data science started from music — so I know it belongs to everyone. I wanted DataJam students to feel that too."
"I used to find messy datasets overwhelming. Now I find them exciting. My goal as a mentor is to help students make that same leap."
"My research is about how people learn. Mentoring through DataJam is where I get to put that into practice with students who are tackling real problems."
"I use data to study the brain. DataJam gives me the chance to inspire students to use data to study anything they're curious about."
"Coming from South Africa, I never imagined I'd be mentoring students across the U.S. in data science. DataJam showed me how universal these skills really are."
"I want to use data to change medicine. Helping students see that connection between a dataset and a real health outcome — that's why I show up."
"I came to UCSD passionate about solving problems through code. DataJam lets me share that drive with students who are just getting started."
"Machine learning opens so many doors. I mentor because I want students to feel that same sense of possibility I felt when I first learned these tools."
"Data science wasn't my first love, but it became one. I want students to discover unexpected passions the way I did."
"As a Women in STEM advocate, I know how important it is for students to see themselves in data science. That's why I mentor."
"I study data science and minor in music. I mentor because I want students to know data science is for curious people — not just coders."
"My capstone is on LLMs in healthcare. But my favorite project is watching a student team have their first 'aha' moment with a real dataset."
Three Programs
The DataJam runs competitions for middle school, high school, and community college students — each designed for that stage of learning.
The DataJam - High School
Teams of 2–8 high school students choose a real-world research question, analyze publicly available datasets, create visualizations, and present their findings to a panel of industry judges.
- Sign up: Late August – January
- Proposal deadline: Early February
- Posters due: Late March
- Finale Presentation: Late April (Zoom)
The DataJam - Community College
A semester-long competition for community college students to explore data science across any subject area. Teams work with university student mentors and build portfolios for future employers.
- Sign up: August (Fall) / January (Spring)
- Proposal deadline: October (Fall) / March (Spring)
- Posters due: November (Fall) / April (Spring)
- Finale Presentation: December (Fall) / April (Spring)
The DataJam - Middle School Days
Half-day in-person workshops introducing middle school students to data analysis through engaging, real-world topics. No prior experience required — mentors guide every step.
- Dates: Fall & Spring semesters
- Format: Half-day in-person workshops
- Mentors guide every group
- Finale Presentation: end of workshop day
Timeline
Follow the steps below to take your team from sign-up to The DataJam Finale.
Sign-up
Each team needs to fill out the online sign-up form on The DataJam website and student permission slips on page 8 & 9 to be sent to datajam@thedatajam.org. The sign-up form will ask (1) advisor name and email, (2) team name, (3) student names and emails (4) availability to meet with a mentor. If you are signing up more than one team with the same advisor, please fill out one form for each team. DO NOT fill out all teams on one form. *Note that it is best to provide a non-school email address on the permission slip as many schools block outside emails, such as those from The DataJam and Slack.
Submit your proposal
There is a rolling deadline for teams to turn in The DataJam proposals. Use the proposal template on page 7 of this guidebook and submit it to the High School online proposal form on The DataJam’s website. Your team will receive feedback from The DataJam and further guidance on your proposed project within a week after your proposal is turned in. Proposals for the 2026–27 High School DataJam MUST BE SUBMITTED BY JANUARY 29, 2027
Projects Underway
Teams work on The DataJam projects. The DataJam mentors are available to meet with your team by Zoom or a videoconferencing service that works best for your team. The times submitted in the sign-up form will be used to match you with a mentor. Once you have a team mentor you can communicate with them regularly on the 2026–27 High School DataJam Slack workspace.
Submit your Poster
The DataJam posters are due. Follow the instructions on page 10 of this guidebook. Posters should be 24” x 36” in size and saved as a pdf file. They should be submitted to the High School posters form on The DataJam website. If the poster submission deadline is during a holiday break for your school, please make arrangements to submit your poster BEFORE your school holiday.
Submit your Presentations and Attend a Judging Session
Final slide presentations will be scheduled for each team at a time that works for both the team and the three-judge panel, who will be listening to each team. The DataJam will send a form to schedule your final presentation time. The final presentations will be held on Zoom. Teams are to submit their presentation slides to the presentation form on The DataJam’s website at least 24 hours before their presentation is scheduled.
Finale
The DataJam - High School Finale will be held on Thursday, April 22, 2027 from 5:30-7:00 PM ET (2:30-4:00 PM PT), on Zoom: https://pitt.zoom.us/j/94389494426. The DataJam teams, parents, teachers, mentors, and all who are interested are invited to attend. The DataJam team projects will be presented, and a variety of awards will be given!
What Your Team Needs
2–8
Students per team
1
Teacher or advisor
Free
No cost to join
No prior data science experience required. Your team will be matched with a college student mentor who will guide you through every step — from choosing a research question to presenting your findings.
Upcoming Events
Join our community events and take your data skills to the next level
The DataJam - Community College Finale — Fall 2026
Coming SoonWatch here as the students present all of their hard work and findings, discovering new insights using data analysis!
The DataJam - High School Finale 2027
Coming SoonWatch here as the students present all of their hard work and findings, discovering new insights using data analysis!
The DataJam - Community College Finale — Spring 2027
Coming SoonWatch here as the students present all of their hard work and findings, discovering new insights using data analysis!
Past Student Projects
A hallmark of The DataJam is that every team chooses their own research question. Select a program and year to explore what students investigated.
Showing 10 of 51 projects in 2026
Curious how these posters come together? Visit our Resources page for the guides and templates teams use to build them.
Data Dialogues
Open conversations about data science, education, and career paths. Featuring guest speakers from industry and academia sharing insights with our community.
Data Dialog #1: Yuting Duan on Data Science and Community Impact
In the first installment of Data Dialogs, Yuting Duan shares insights on data science, community engagement, and inspiring the next generation of data enthusiasts.
Data Dialog #2: Vaishnavi Akella on Student-Led Data Projects
Vaishnavi Akella joins Data Dialogs to discuss the power of student-led data projects and how young analysts can make a real-world difference.
Data Dialog #3: Bob Moreland on Data Education and Mentorship
Bob Moreland shares his experience in data education and mentorship, discussing how to build meaningful learning experiences around data literacy.
Data Dialog #4: Jatin Singh on Analytics and Career Pathways
Jatin Singh discusses career pathways in analytics, the skills employers look for, and how students can prepare for data-driven careers.
Data Dialog #5: Yunge Xiao on Data Visualization and Storytelling
Yunge Xiao explores the art of data visualization and storytelling, sharing techniques for making data accessible and compelling.
Data Dialog #6: Florence Hudson on Big Data, Ethics, and Public Impact
Florence Hudson, Executive Director of the NSF Northeast Big Data Innovation Hub, discusses big data in the public sector, data ethics, and her career journey from aerospace engineering to leading national data initiatives.
Data Dialog #7: Tony Robol on Data Leadership and Community Engagement
Tony Robol joins Data Dialogs to share insights on data leadership, building data-literate communities, and the role of mentorship in shaping the next generation of data professionals.
Data Dialog #8: Paul Hansford on Data in the Public Sector
Paul Hansford discusses data applications in the public sector, civic technology, and how open data can empower communities.
Data Dialog #9: Amapola Garcia on Data for Social Good
Amapola Garcia talks about using data science for social good, equity in data access, and building inclusive data communities.
Data Dialog #10: Ajeet Subramanian on Machine Learning and Innovation
Ajeet Subramanian discusses machine learning, innovation in data science, and how students can get started with advanced analytics.
The DataJam in Action
Over a decade of real students asking real questions — from Pittsburgh classrooms to teams competing nationally and internationally.
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