Star House, a nonprofit organization that serves homeless and at-risk youth in Columbus, Ohio, faces various challenges in fulfilling its mission. For example, it may struggle to provide adequate support and resources to young people in need, especially as the number of homeless youth continues to rise.

To help address these challenges, JPMorgan Chase hosted a hackathon to find innovative solutions to the problems faced by Star House. The hackathon brought together a diverse group of people, including developers, designers, and subject matter experts, to collaborate and develop technology-based solutions that could help Star House better serve its clients. By leveraging the power of technology, JPMorgan Chase and the participants in the hackathon aimed to help Star House overcome its challenges and make a positive impact on the lives of homeless and at-risk youth.

For the JPMorgan Chase hackathon, a team of six students from across the United States (including me) came together to tackle the problem of locating the best sites for youth homeless shelters. Our team applied Agile and Scrum methodologies to rapidly prototype and iterate on their solution.

To gather and analyze data, the team utilized their data skills, including proficiency in Pandas and Python. They collected and analyzed data on various factors that could impact the success of a youth homeless shelter, such as access to public transportation, proximity to schools and job opportunities, and the presence of community resources.

Using this data, the team developed a sophisticated algorithm to determine the most optimal locations for new shelters. Their solution was well received by the hackathon judges and was recognized for its innovative and data-driven approach to addressing the problem of youth homelessness.

The team's findings utilized heat maps and in-depth location analysis to locate the best probable areas for a homeless shelter. The heat maps visually represented the density of various factors that were deemed important for the success of a homeless shelter, such as access to public transportation, proximity to schools and job opportunities, and the presence of community resources.

The depth analysis involved the use of statistical methods and data visualization techniques to further examine the relationship between these factors and the likelihood of a successful shelter. The results of this analysis allowed the team to identify specific areas that scored high in all the important factors, making them the best probable locations for a homeless shelter. The team's use of heat maps and depth analysis provided a clear and compelling picture of the optimal areas for a homeless shelter and helped to inform decision-making around the placement of these critical resources.

Below shows our submitted pitch deck towards judges from Star House & JPMorgan Chase.

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