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Data Snax Datathon in St. Louis

devpostHosted on Devpost

Fetched 3 months ago

Saturday, April 18, 2026

to Saturday, April 18, 2026

Data ScienceArtificial IntelligenceWeb Development
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.

Event Type

in person

4

Participants

$375

Prize Pool

0

Est. Projects

Welcome to Data Snax Datathon 2026!

Culminate STL TechWeek at DataSnax’s 2nd annual Datathon on April 18th at the University of Health Sciences and Pharmacy in St. Louis
On April 18th from 2-6 pm, join us for a collaborative competition where participants will work in teams to solve real-world, data-driven challenges. It’s a great chance to sharpen your skills, learn from others, and have fun tackling problems together.
For questions or assistance with the application, contact:
📧 danniel.franco@uhsp.edu
📞 (314) 267-3051
Data Snax is here to welcome students interested in data and computer science. Our goal is to connect you with opportunities to explore, engage, and grow through hands-on activities and campus resources

Sponsors

Major League Hacking (MLH) – Global Partner image

Major League Hacking (MLH) – Global Partner

mlh.io

STL TechWeek image

STL TechWeek

techstl.com

InfraGard St. Louis Alliance image

InfraGard St. Louis Alliance

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct