Quant jobs / JPMorgan

Analyst – Wholesale Credit Risk Quantitative Research

An entry-level credit risk modelling role in JPMorgan's wholesale credit quant team. You build loss forecasting models for stress testing and loan loss reserves.

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.

Develop loss forecasting models for regulatory use
Run back-testing and annual model reviews
Clean and engineer features from large panel datasets
Implement models with data and technology partners
Write documentation for internal and regulatory review

What they ask for

Required

Quantitative degree
Calculus, linear algebra, probability and statistics
GLMs, time series, clustering, trees and logistic regression
Panel data experience
Object-oriented programming and Python or C++
Communication

Preferred

Wholesale credit and loss forecasting knowledge
Securitisation products such as RMBS, ABS, CLOs
Bond and loan pricing
Machine learning and generative AI
SQL and cloud tools

Education: Degree in engineering, financial engineering, CS, maths, sciences, statistics or econometrics
Experience: New graduates welcome; 2+ years preferred
Languages and tools: Python
C++
SQL
Markets: credit

How to prepare

Fit and back-test a logistic PD model on public loan data
Learn how CECL and stress-test loss forecasting work
Practise cleaning panel data and engineering time-lagged features
Review how model documentation is structured for validators

What to study

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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.