all students—undergraduate or graduate—currently enrolled in two- or four-year degree granting programs at accredited not-for-profit colleges or universities located in the United States,
recent college graduates, as of December 31, 2022, in the United States.
All ventures must have at least two and no more than six team members.
The Team Leader serves as the main contact for the team and must complete the team's application. The application must demonstrate that the Team Leader played a significant role in conceiving the venture.
Team members must:
demonstrate commitment to moving venture forward,
have played a primary role in developing the business strategy,
and have a key management role in the startup venture.
Each team must provide contact information for a faculty advisor/mentor who is familiar with the team and the venture. Any faculty advisor/mentor is welcome but not required to be present at UTSA on pitch day.
The competition is for new, for-profit, independent ventures in the seed, start-up, or early growth stages. Ventures with a social impact focus are eligible as long as there is a revenue-generating component to the venture. Ventures that qualify for 501(c) status are not eligible.
An existing business is eligible only if, as of 11:59 p.m. on December 31, 2022, it has
received less than $25,000 in funding
earned less than $100,000 in gross revenue.
Ventures must be wholly owned by the team (i.e., investor-funded ventures will be disqualified)
Ventures must be student-created and student-managed. Teams are required to provide proof of enrollment or current class schedule for all members at the time of submitting the application. Recent graduates can provide a copy of their diploma, original transcript, or any other document proving their eligibility as of December 31, 2022.
To inspire and prepare a generation of diverse data scientists who can make our world more equitable, informed, and secure.
Mission
In hand with the UTSA Colleges, to educate data science practitioners and scholars at the graduate and postgraduate levels and provide experiential learning at all levels. Lead interdisciplinary data-intensive research that calls for focused data science beyond a single college.