Leveraged machine learning and data science to generate risk parameters beyond credit score using transactions (via Plaid) to assess risk from spending habits.

Internal people analytics platform processing 10M+ data points daily. Used to increase deal-flow, and catch deals before they're known among seed investors

Developed a highly scalable data pipeline using Python, handling the extraction, transformation, and loading of large datasets with efficiency and accuracy.