8 Data Science Competitions for High School Students
Unlike fields tied to specific industries, data science is broadly applicable, influencing areas such as healthcare, business, sports, and environmental studies. For high school students, stepping into this multidisciplinary field can feel overwhelming due to its blend of statistics, programming, and domain expertise. Competitions are a structured and accessible way to make this complexity more manageable.
These events are designed to help you engage with real-world problems, sharpen your technical skills, and develop a practical understanding of the field. They’re also a chance to connect with peers, build a portfolio of work, and add meaningful experiences to your college applications. By focusing on challenges like sports analytics, financial modeling, or energy management, competitions let you apply your knowledge in impactful and relevant ways.
To help get you started, we’ve put together this list of 8 data science competitions for high school students. These events provide a platform to challenge yourself, develop critical skills, and take the first steps toward a future in data science or related fields.
The NFL Big Data Bowl 2025 is a premier competition that invites data enthusiasts to analyze NFL player tracking data and uncover patterns in football strategies. This year’s theme focuses on “Pre-snap to Post-snap” predictions, challenging you to examine pre-snap actions — such as player substitutions, motions, and shifts — and forecast subsequent offensive or defensive plays. Utilizing the NFL’s Next Gen Stats data, your goal is to derive insights that could range from predicting play types (e.g., run versus pass) to identifying defensive schemes or detailing individual player assignments.
Participants can choose from three distinct tracks:
Undergraduate Track: Exclusively for undergraduate students, offering a platform to showcase emerging talent.
Metric Track: Focuses on developing innovative data-driven metrics to assess team or player performance.
Coaching Presentation Track: Aims to translate analytical findings into actionable strategies for coaches, enhancing on-field decision-making.
To foster diversity and inclusion in sports analytics, the NFL offers a mentorship program as part of the Big Data Bowl. This initiative connects experienced NFL analytics experts with novices, providing guidance and support throughout the competition.
The competition is highly competitive, attracting teams and individuals with both technical expertise and football knowledge. Top submissions get to present their findings at the NFL Scouting Combine, where a final winner will receive an additional prize of $12,500. This contest is an excellent chance for high school and college students to showcase their analytical skills, especially in machine learning, data visualization, and statistical modeling, on one of the biggest stages in sports analytics.
Location: Virtual
Prizes: $12,500 each for the top 5 (plus an invitation to present at the 2025 NFL Scouting Combine, where one team wins an additional $12,500), and $5,000 each for ranks 6–10
Eligibility: Open to everyone with a Kaggle account (those under 18 can participate with approved parental or guardian consent but will not be eligible for prizes)
Submission deadline: October 10, 2024 - January 6, 2025
2. LLM - Detect AI Generated Text
The LLM - Detect AI Generated Text competition presents a unique opportunity to develop models capable of distinguishing between human-written essays and those generated by large language models (LLMs). As LLMs produce text closely resembling human writing, this challenge requires innovative detection techniques to identify subtle patterns unique to machine-generated content. You’ll work with a dataset comprising both student essays and AI-generated text on various topics. The competition’s focus on plagiarism and educational integrity is timely as educators grapple with the potential impact of LLMs on students’ writing skills and originality.
As a participant, you’ll compete for significant cash prizes, with the top leaderboard prizes ranging from $5,000 to $20,000, as well as efficiency prizes for streamlined models. Winning entries will be judged based on their accuracy, specifically the area under the ROC curve, assessing the model’s ability to classify text correctly. This competition is a great opportunity for high school students interested in natural language processing (NLP), machine learning, and ethical AI applications, providing a contemporary challenge with educational and societal relevance. The competitive environment and practical nature of this contest make it highly prestigious in the data science community.
Location: Virtual
Prizes: $5,000 - $20,000
Eligibility: Open to everyone with a Kaggle account (those under 18 can participate with approved parental or guardian consent)
Submission deadline: January 23 (tentative, based on the 2024 competition)
3. Temple University’s OwlHacks
Temple University’s OwlHacks is an annual, student-organized hackathon where you can collaborate, innovate, and address various data science challenges head-on. The event is designed to accommodate participants of all skill levels, so it’s a great setting to network, attend workshops, and expand your expertise. The hackathon has themed project tracks such as Smart Health, Urban Tech, and Inclusive Education, encouraging the development of solutions that have tangible societal impacts. The Finance ML Challenge is an excellent choice if you're interested in data science and machine learning, giving you a chance to tackle complex financial problems alongside other data enthusiasts.
The hackathon features workshops led by industry professionals and faculty members, covering topics like personal branding, technical skills, and professional development. Mentorship is also available to guide teams throughout the event. Prizes at OwlHacks add a competitive incentive, ranging from gift cards and hardware kits to unique industry-sponsored awards like the Best Use of Adobe Express prize, which includes a Wacom tablet and JBL speaker. The competition accommodates individual participants and teams, with up to five people allowed per team, so you can choose whether to tackle challenges solo or join together with others.
Location: Temple University’s Science Education and Research Center (SERC), Philadelphia, PA
Prizes: Various awards, including gift cards, hardware kits, and industry-sponsored prizes
Eligibility: Open to everyone
Competition dates: October 5 - 6 (tentative, based on the 2024 competition)
Application deadline: Rolling admissions, but early registration is encouraged due to limited spots
4. Enefit - Predict Energy Behavior of Prosumers
The Enefit - Predict Energy Behavior of Prosumers competition invites high school students to address a significant challenge in the energy sector: forecasting the energy consumption and production patterns of prosumers — individuals or entities that both produce and consume energy. The unpredictable behavior of prosumers can lead to energy imbalances, posing logistical and financial challenges for energy providers. This competition aims to develop accurate predictive models to mitigate these imbalances, thereby enhancing the efficiency and sustainability of energy management systems.
You’ll be tasked with building time series prediction models that analyze various factors influencing prosumer behavior, such as weather conditions, energy prices, and historical consumption data. The competition’s structured approach includes a training phase where your model will be fine-tuned, followed by an evaluation phase against future data, emphasizing the relevance and applicability of your predictions.
Substantial prizes are awarded to top submissions, with the first-place winner receiving $15,000. To participate, you’ll need to meet specific technical requirements, such as CPU and GPU runtime limits and working with publicly available datasets. Teams of up to five are allowed, allowing you to engage in collaborative problem-solving while applying data science skills to real-world energy dynamics.
Location: Virtual
Prizes: $5,000 - $15,000
Eligibility: Open to everyone with a Kaggle account (those under 18 can participate with approved parental or guardian consent)
Submission deadline: May 1 (tentative, based on the 2024 competition)
5. MachineHack’s Data-Centric AI Competition
MachineHack’s Data-Centric AI Competition, in collaboration with Cleanlab, is a multi-stage challenge for those looking to enhance their machine-learning skills by focusing on data quality and its impact on model performance. Unlike traditional competitions that emphasize model architecture, this challenge encourages you to improve datasets by identifying and correcting errors, handling outliers, and refining data labeling.
The competition is divided into two phases:
Text Data Phase: Over five weeks, you'll work with a dataset of Amazon reviews, aiming to build and optimize a classification model that predicts star ratings based on review content. This phase emphasizes natural language processing techniques and the importance of clean textual data.
Image Data Phase: In the subsequent three weeks, the focus shifts to an alphanumeric character image dataset. Your task is to construct and fine-tune a classification model capable of accurately identifying character types from the given images, highlighting the significance of high-quality image data in machine learning.
Prizes and recognition add a competitive edge with prestigious awards for top-performing models. The competition is open to data science enthusiasts from various backgrounds, so even high school students can participate if they’re eager to learn and showcase their skills. You can expect to work with 17,000 training examples for the text-based task and 9,500 for the image-based task, and each phase includes a private test set to truly assess your model’s accuracy.
Location: Virtual
Prizes: $3,000
Eligibility: Open to everyone with a MachineHack account
Competition dates and submission deadline: To be announced
6. Saint Joseph’s University’s Analytics and Data Visualization Competition
Saint Joseph’s University’s Analytics and Data Visualization Competition is an engaging, multi-stage competition inviting high school students to delve into data analysis and create insightful visualizations. Over a six-week period, explore a dataset to uncover hidden patterns and trends, culminating in a one-day, in-person event at the Haub School of Business. Here, participants present their findings to a panel of judges comprising esteemed academics and industry experts in Business Intelligence & Analytics.
With resources like on-demand tutorials, access to mentors from Saint Joseph’s University, and live feedback sessions, you’re fully supported in developing both technical and presentation skills. The competition emphasizes real-world applications of data science, fostering skills in data analysis, storytelling, and teamwork — essential competencies in analytics and various other fields. It is open to high school students from the local area, making it accessible even to those beginning their journey in data science. Judges assess not only technical insights but also the effectiveness of communication, placing a strong emphasis on critical thinking and narrative development.
Location: Virtual sessions followed by an in-person event at Saint Joseph's University - Hawk Hill Campus, Philadelphia, PA
Prizes: $2,500 (tentative, based on previous competition)
Eligibility: High school students from local area schools
Competition dates:
Round 1: February 26, 2025 (virtual over Zoom for all teams)
Round 2: March 12, 2025 (in person at Hawk Hill campus for top teams)
Application deadline: December 20, 2024
7. MathWorks Math Modelling Challenge
MathWorks Math Modeling Challenge (M3 Challenge) is a fast-paced, team-based competition designed for U.S. high school juniors and seniors to apply mathematical modeling to real-world problems. Organized by the Society for Industrial and Applied Mathematics (SIAM) and sponsored by MathWorks, the M3 Challenge emphasizes the importance of mathematics and data analysis in addressing contemporary issues. No advanced skills are required — just a solid foundation in math, critical thinking, and teamwork.
During the competition weekend, teams of three to five students have 14 consecutive hours to develop a solution to a previously undisclosed problem. This format encourages collaboration, critical thinking, and effective time management. Participants are provided with free resources, including access to MATLAB software, to assist in their modeling efforts.
The M3 Challenge is widely recognized and competitive, attracting teams from across the U.S. and the U.K. Top-performing teams are awarded scholarships totaling over $100,000, with finalists invited to present their solutions in New York City. Not only will you have the chance to win scholarships, but you can also compete for additional coding-related awards if your solution includes technical computing.
Location: Virtual
Eligibility: High school juniors and seniors in the U.S. and sixth-form students (ages 16-19) in England and Wales
Prize: Various prizes totaling over $100,000
Competition dates: February 28 - March 3, 2025
Application deadline: February 21, 2025
DataCrunch is a dynamic data science competition series that focuses on finance, machine learning, or predictive modeling. Founded by a team of Paris-based students and a former finance instructor, DataCrunch offers weekly “sprints” where you can develop models based on real financial datasets. The primary objective is to create accurate predictive models, with the top three models each round gaining entry into Data Crunch’s Arena. As long as your model ranks at the top, you’ll receive a 200€ monthly reward, making this a unique chance to not only test your skills but also earn cash on the side!
Each week’s challenge introduces a new dataset for building algorithms that can tackle real investment scenarios, offering a fresh opportunity to practice and refine your work. DataCrunch is open to various experience levels, so if you have some Python or machine learning knowledge, you’re set to participate. If you’re aiming to apply technical skills in a real-world context and compete for cash prizes, this competition could be a worthwhile option to explore.
Location: Virtual
Prizes: €200 ($211) monthly to the top 3 models
Eligibility: Open to everyone; prior knowledge of machine learning and statistics is recommended.
Competition dates: Weekly
Application deadline: Rolling admissions
If you’re looking to build a project/research paper in the field of AI & ML, consider applying to Veritas AI!
Veritas AI is founded by Harvard graduate students. Through the programs, you get a chance to work 1:1 with mentors from universities like Harvard, Stanford, MIT, and more to create unique, personalized projects. In the past year, we had over 1000 students learn AI & ML with us. You can apply here!
Tyler Moulton is Head of Academics and Veritas AI Partnerships with 6 years of experience in education consulting, teaching, and astronomy research at Harvard and the University of Cambridge, where they developed a passion for machine learning and artificial intelligence. Tyler is passionate about connecting high-achieving students to advanced AI techniques and helping them build independent, real-world projects in the field of AI!
Image Source - NFL Big Data Bowl Logo