Associate Consumer Loan Modeling Quant
Associate Consumer Loan Modeling Quant
Location: FL/NYC
Summary: A leading hedge fund is expanding its quantitative research team with a new hire focused on consumer credit modeling. This firm is known for its deep expertise in mortgage and consumer credit markets, and its integrated approach to investment, analytics, and loan servicing. The team is seeking an Associate-level Quantitative Researcher/Strategist to join their Consumer Modeling group. This is a high-impact role where you'll work cross-functionally with investment, risk, and strategy teams to build and enhance credit risk models and data pipelines. The team is collaborative, data-driven, and committed to innovation in credit analytics. This is a unique opportunity to shape the modeling infrastructure of a growing platform and contribute to the development of new consumer lending strategies.
Key Responsibilities:
- Build and apply statistical and machine learning models to analyze credit performance, borrower behavior, and forecast future outcomes
- Analyze diverse consumer and small business financial products (e.g., mortgages, personal, auto, and student loans) to support investment decisions
- Develop and maintain cash flow models and evaluate investment cash flows across credit assets
- Manage and ensure quality of large datasets using programming tools (Python, R, SQL) and strong data processes
- Communicate insights clearly to both technical and non-technical stakeholders while working independently and in a fast-paced team environment
Job Requirements:
- Bachelor's degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Data Science)
- Experience working within the consumer loan space [auto loans, student loans, credit card loans, solar loans, etc.]
- Familiarity with loan-level data and performance analytics
- Strong programming skills in Python and SQL
- Proven experience building credit models and working with statistical frameworks
- Excellent communication skills and the ability to work across teams
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