Wholesale Credit Grading -VP

TwinThread; Mumbai; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

TwinThread is seeking a VP for the Wholesale Credit Grading team to enhance risk management by building and owning credit rating models for CCAR and CECL. The role involves applying advanced statistical and econometric methods, along with AI/ML techniques for robust forecasting and monitoring.

The ideal candidate will have a quantitative degree and at least 4 years of relevant experience. Strong skills in Python and knowledge of credit risk modeling are essential. TwinThread values diversity and provides an inclusive work environment.

Qualifications

• Strong applied statistics and econometrics skills.
• Experience with large-scale panel datasets and data engineering.
• 4+ years of relevant experience preferred.

Responsibilities

• Build and own credit rating models for CCAR and CECL.
• Apply AI/ML for forecasting and risk monitoring.
• Prepare documentation for regulatory reviews.

Skills

Applied statistics

Machine Learning experience

Python programming

Credit risk modeling knowledge

Education

Quantitative degree (Engineering, Financial Engineering, Computer Science, Mathematics, Statistics)

Tools

SQL

Distributed data tools

Job description

VP - Wholesale Credit Grading team

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 explainability; productingize 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.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. 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. Visit our FAQs for more information about requesting an accommodation.