Wholesale Credit Grading -VP

Testing Site - JPMC; Mumbai; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

JPMorganChase is seeking a Quantitative Research professional in Wholesale Credit Risk Modeling. You will build end-to-end credit rating models, apply advanced statistics and ML to forecasting, and prepare regulatory-grade documentation for reviews.

The role emphasizes working with large data, robust governance, and collaboration with Risk and Tech groups to strengthen risk insights.

Qualifications

• Strong applied statistics/econometrics
• Experience with ML and generative AI
• Hands-on Python with good software practices (version control, testing)
• Experience with large-scale panel datasets and feature engineering
• Foundational credit risk modeling knowledge and regulatory-grade documentation
• 4+ years relevant experience preferred

Responsibilities

• Build and own wholesale credit rating models end-to-end (PD/LGD/EAD, rating transitions)
• Apply statistics/econometrics and targeted AI/ML for forecasting and risk monitoring
• Prepare clear documentation for regulatory/internal reviews; present results to senior risk committees

Skills

Statistics

Python

ML/AI

Documentation

Data cleaning

Version control

Education

Engineering/Financial Engineering/CS/Math/Statistics/Econometrics

Tools

SQL

Cloud data tools

Job description

Bring your expertise to JPMorganChase. As part of Risk Management and Compliance, you’ll help keep the firm strong and resilient by anticipating emerging risks and applying sound judgment to solve real-world challenges for our company, customers, and communities. Our culture values curiosity, challenging the status quo, and striving to be best-in-class. As a member of the Quantitative Research team for Wholesale Credit Risk Modeling, you will work alongside experienced researchers and business partners, deepening both your quantitative toolkit and your business acumen.

What you’ll do

• Build and own wholesale credit rating models end-to-end (PD/LGD/EAD, rating transitions) supporting credit business, CCAR and CECL, with rigorous back testing, monitoring, and model governance.
• Apply stats/econometrics and targeted AI/ML for forecasting, risk monitoring, and explain ability; product ionize with robust data pipelines and controls in partnership with Data/Tech.
• Prepare clear, comprehensive documentation for regulatory and internal reviews; present results and model impacts to senior risk committees.

Required qualifications, capabilities, and skills

• Quantitative degree (Engineering, Financial Engineering, Computer Science, Mathematics, Statistics, Econometrics).
• Strong applied statistics/econometrics (GLMs, logistic regression, time series; familiarity with trees/clustering.
• Experience in ML and generative AI.
• Experience working with large-scale panel datasets, including data cleaning, filtering and feature engineering.
• Hands-on Python with good software practices (version control, testing, reproducibility).
• Foundational credit risk modeling knowledge and experience writing regulatory-grade documentation.
• 4+ years relevant experience preferred.

Preferred qualifications, capabilities, and skills

• Wholesale Credit experience; experience with credit scorecards and rating systems.
• Beneficial: SQL and distributed data tools; cloud-based workflows.

Beyond your technical skills, we value the qualities that make you unique - your personal attributes, interests, and achievements beyond academia and professional roles that demonstrate who you are and the impact you can bring to our team.