WCR - Quantitative Research Analyst

Fairygodboss; Mumbai; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Fairygodboss is seeking a Quantitative Research Analyst to join their Wholesale Credit Risk group in Mumbai, India. You will develop and manage quantitative models for counterparty credit risk while collaborating with tech partners and control teams.

The ideal candidate should have 1-3 years of relevant experience, strong programming skills in Python & R, and a Master's/Ph.D. in a quantitative discipline. We offer a diverse and inclusive workplace.

Qualifications

• 1-3 years of experience in Quantitative Research or Risk Modeling roles.
• Familiarity with counterparty risk domain preferred.
• Knowledge of financial instruments like OTC derivatives and Futures & Options.
• Strong programming skills in Python & R.

Responsibilities

• Develop and enhance the SSE framework for managing counterparty risk.
• Quantify risks not captured in existing stress scenarios.
• Monitor and govern the calculation framework.
• Collaborate with global QR teams.

Skills

Quantitative Research

Risk Modeling

Python

R

Problem-Solving

Communication

Education

Master’s/Ph.D. in Financial Engineering, Operations Research, Statistics, Mathematics, Computer Science, Economics

Tools

C++

Job description

Job Description

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

As a Quantitative Research Analyst within Wholesale Credit Risk group, you will work in the newly formed Counterparty Credit Risk QR team that designs, manages & owns quantitative models and risk limit metrics such as Strategic Stressed Exposure (SSE), Potential Future Exposure. The team also owns back‑testing procedures to control the risk associated with Central Clearing Counterparties (CCP).

The mandate of CCR QR team is actively expanding with current scope including:

• Manage enhancements to the SSE framework which governs the computation, scenario design and monitoring as well as the impact quantification of risk drivers not being stressed adequately (Risk not in Stress).
• Develop statistical models and tools for the assessment and management of counterparty credit risk covering CCP related risk.
• Design and implement software framework for counterparty credit risk in Python, delivering results through dashboards.
• Partner with control teams for ongoing model and risk governance.
• Engage tech partners to deploy models to front end solutions.

Your key responsibilities in the role will include:

• Develop, support and enhance the SSE framework & its components that are used in managing counterparty risk stemming from the trading book.
• Build understanding of Risk not in Stress (RNIS) framework by identifying & quantifying the impact of the risks not captured in existing stress scenarios.
• Leverage firm’s infrastructure to perform quantitative analysis on the JPMSE portfolio.
• Jointly manage the life cycle of models with our risk and technology partners.
• Ongoing performance monitoring and governance of the calculation framework.
• Closely cooperate with the QR teams across the globe.
• Document modeling choices, theoretical arguments, testing and results.

Requirements

• Demonstrable relevant 1-3 years experience in Quantitative Research or Risk Modeling roles with an investment bank or financial institution. Familiarity with counterparty risk domain is preferred.
• Strong educational background in Quantitative discipline such as Master’s/Ph.D. in Financial Engineering, Operations Research, Statistics, Mathematics, Computer Science, Economics, or related field of study.
• Knowledge of financial instruments like OTC derivatives, Futures & Options, and Securities Financing Transaction (SFTs), along with understanding of risk management methodologies (VaR and stress testing) across all asset classes is highly preferred.
• Substantial programming skills expertise in Python & R. Working knowledge of C++ is preferred.
• Familiarity with AI agentic coding would be a plus.
• Strong analytical mindset with excellent problem‑solving and data interpretation skills.
• Excellent communication skills with ability to verbally & logically articulate complex information. Interpersonal skills will be useful as projects can require interaction & synchronization with other teams.

About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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.

About The Team

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.