Quant Modeling [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

This role focuses on validating forecasting and other models used in consumer lending portfolios, including CCAR and CECL models. It involves assessing conceptual soundness, designing tests, comparing outputs, communicating findings to stakeholders and regulators, monitoring performance, and ensuring compliance with SR 11-7. The role also involves educating junior team members.

What you'd actually do

  1. Drive validation of forecasting models for consumer lending portfolio including Comprehensive Capital Analysis and Review (CCAR) and Current Expected Credit Loss (CECL) models.
  2. Drive validation of all models used in consumer lending portfolio such as underwriting, pricing, collateral evaluations, collection and recoveries.
  3. Assess consumer credit lending models by evaluating conceptual soundness, assumptions, input reliability, and outcomes.
  4. Design and execute tests for scenario analysis, loss forecasting, stability, and sensitivity for model components.
  5. Communicate validation results and model risk issues to Model Developers, Risk, Finance, Control teams, and Internal Audit.

Skills

Required

  • Developing or validating models for financial institutions including stress test models, allowance models, and models used in consumer retail lending
  • Performing statistical analysis including logistic regression, multivariate regression, classification methods, cohort analysis, predictive modeling, quantitative analysis of time series and panel data using econometric methodologies and machine learning analysis including XGBoost, applied to consumer retail lending models
  • Designing, developing, and automating model validation quantitative analysis for consumer lending stress test and consumer retail models using SAS and Python, including coding scripts to extract, analyze, and visualize model results with Python libraries including pandas, numpy, pyspark, scikit-learn, and statsmodels
  • Reviewing model outputs, monitoring model performance, identifying model risk issues, and escalating findings for resolution in consumer lending
  • Ensuring compliance with CCAR, CECL, and SR 11-7 model risk management standards during model validation and review as applied to consumer lending products

Nice to have

  • PhD in Economics, Mathematics, Statistics, Data Science, Mathematical Finance, or related field of study
  • SAS
  • Python
  • pandas
  • numpy
  • pyspark
  • scikit-learn
  • statsmodels

What the JD emphasized

  • SR 11-7: Guidance on Model Risk Management
  • CCAR
  • CECL
  • model validation
  • consumer lending