Quantitative Trading and Research - Securitized Products Group - Associate

Job Summary As an Associate in the Securitized Products Group (SPG) Quantitative Trading & Research Team, you will sit within the non‑agency RMBS modeling team and partner closely with SPG trading desks to support modeling, valuation, market‑making, and risk assessment. You will help drive the modernization of credit modeling by applying machine learning and generative AI across the model development lifecycle, including data processing and exploration, model calibration, performance monitoring, and delivery of analytics and reporting tools. You will collaborate with stakeholders across business, technology, market risk, and other partner teams to develop new models and enhance existing capabilities, improve understanding of model behavior and trading insights, ensure robust model infrastructure and controlled usage, and provide subject‑matter expertise, training, and guidance to internal users and external clients. Job Responsibilities Develop and support advanced financial models for RMBS, enabling business portfolio management, trading, hedging, and risk assessment. Conduct model back‑testing, performance tracking, and provide business insights to inform portfolio management and trading strategies. Perform large‑scale data queries, processing, and machine‑learning analysis for RMBS prepayment and credit modeling using high‑quality calibration data. Build and optimize robust platforms for large‑scale data analysis to support various modeling initiatives. Develop new models and analytical tools, and implement them within our advanced, high‑performing mortgage loan/bond pricing and analytics framework. Design and implement analytical tools to monitor model performance and market conditions in Residential Mortgage‑Backed Securities (RMBS), enhancing business decision‑making processes. Oversee the maintenance and enhancement of existing infrastructure used for valuation and hedging of financial transactions. Provide support to internal and external clients regarding model usage, addressing inquiries and facilitating training as needed. Collaborate closely with risk and model review groups to ensure proper model usage, conduct model reviews, and implement effective risk controls. Required Qualifications, Capabilities, and Skills Quantitative educational background: Master’s or PhD degree in a quantitative field. Advanced modeling skills in developing machine learning, statistical, or econometric models, preferably with applications in financial fields. Strong programming skills in Python (C++ is a plus); proficiency in statistical Python packages such as NumPy, Pandas, and stats packages (StatsModels, scikit‑learn, SciPy, etc.) for data manipulation and statistical analysis. Experience working with large‑scale databases (e.g., PostgreSQL, Redshift) for machine‑learning analysis and modeling is desirable. Preferred Qualifications, Capabilities, and Skills Experience in data analysis focused on mortgage and loan performance datasets, specifically analyzing prepayment and credit historical data at the loan or facility level, is desirable. About the Team J.P. Morgan’s Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. The SPG Quantitative Trading & Research Team is a high‑performing quantitative modeling organization focused on Residential Mortgage‑Backed Securities and related structured products. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. #J-18808-Ljbffr