Quant jobs / JPMorgan

Applied AI/ML Lead – Consumer Risk Modeling

A senior hands-on modelling lead in Chase consumer risk modelling, covering credit card and small business portfolios. You build and run ML models for decisions such as underwriting and segmentation.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Design ML and statistical models for segmentation, underwriting and portfolio strategy
Use big data and cloud platforms to speed up model development
Define the modelling roadmap with senior stakeholders
Support validation, monitoring and governance of production models
Mentor junior modellers and use generative AI responsibly in workflows

What they ask for

Required

Advanced degree in a quantitative field
8+ years building predictive risk models in financial institutions
Applied ML and generative AI
Distributed computing and big data
Model governance awareness
Stakeholder communication

Education: Advanced degree in maths, statistics, CS, OR, econometrics, physics or similar (or equivalent experience)
Experience: 8+ years developing predictive risk models in financial institutions
Markets: credit

How to prepare

Build a credit scoring model with gradient boosting and explain it with SHAP
Study model fairness and fair lending rules
Learn Spark-style distributed feature engineering
Review how model monitoring detects drift

What to study

The Risk Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on JPMorgan’s site before applying: requirements, location and pay can change after we check them.

View the posting on JPMorgan’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with JPMorgan and doesn’t handle applications.