Match Optimization Summer Associate
Project Description:
The Bloomberg Harvard City Hall Fellowship match process is critical for fellow placement and overall program success. It follows the application processes for students and cities and is intended to initiate the city-fellow interviews, the final step in the application process.
The current process that pairs student candidates with host cities has been manual, complex, and leverages multiple software programs. There are various inputs that exist across the application processes for both students and host cities that contribute to successful matches. This data could be collected in a more structured way to help feed into a more rigorous and data driven model, including one that would help to overcome biases. A high degree of trust will be imperative for this position as the Summer Associate will have access to sensitive information.
Tasks and Deliverables:
- Develop data-driven model that could inform and streamline manual efforts to create a more efficient fellowship match process.
- Access and analyze multiple cohorts of historic data to build and test the model.
Desired Qualifications and Experience:
- Strong data analytics/statistical background or experience
- An interest in process improvements
- Curiosity about operational innovation
Compensation: $21-$25/hour
