Sumedh Ambokar — Operations Associate

I am an experienced post-PhD quantitative modeler using large and complex data sets, coding languages like Python, SQL, R and cloud-based technologies like Spark, AWS and Databricks. I analyze existing model outputs to identify and test hypotheses, which I use to build and improve predictive econometric models to predict consumer credit default events and amounts. I use these models in loss forecasting, quarterly allowance, CECL and DFAST stress testing of Capital One's US credit card portfolio of over $150 billion. I interact with all the internal stakeholders/cross-functional partner teams and present data-driven stories and recommendations to influence senior leadership decisions. Previously, I graduated with a PhD in Economics from the University of Pennsylvania with a thesis estimating the search costs of US mortgage borrowers, statistical discrimination by lenders and its impact on monetary policy transmission to consumption. I also did an internship at AQR Capital in the fixed income research group evaluating term structure model estimation by linear regression. I was a quantitative strategist in the investment banking division of Goldman Sachs after a MBA at Indian Institute of Management, Ahmedabad (IIMA). I was also a software developer at Oracle after completing a Bachelor and Master of Technology at Indian Institute of Technology, Bombay (IITB).

Stackforce AI infers this person is a Fintech quantitative modeler specializing in credit risk analysis and predictive modeling.

Location: San Francisco, California, United States

Experience: 7 yrs 6 mos