Wholesale Credit Quantitative Research - Analyst

Testing Site - JPMC; Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

JPMorganChase in Mumbai is seeking a Wholesale Credit Quantitative Research Analyst to design and implement quantitative models that support CCAR, ICAAP, and loan loss reserves. You will work with experienced researchers to improve forecasting and risk assessment.

The role is based at Nirlon Knowledge Park, Goregaon (East), Mumbai. Applicants should have engineering/quantitative degrees and strong skills in calculus, linear algebra, statistics, and Python or R, with 1–3 years’ experience.

Qualifications

• Degree in Engineering, Financial Engineering, Computer Science, Mathematics, Statistics, Econometrics or other quantitative fields.
• Strong background in Calculus, Linear Algebra, Probability, and Statistics.
• Knowledge of statistical methods: GLMs, time-series, clustering, decision trees, logistic regression.
• Experience handling large panel data and data cleaning/filtering.
• Proficiency in Python or R.
• Ability to solve problems creatively in a dynamic environment.
• 1–3 years of relevant experience preferred.

Responsibilities

• Design and develop PPNR forecasting models for regulatory purposes.

Skills

Python or R

Statistics

Time-series analysis

Calculus

Linear Algebra

Decision trees

Logistic regression

Education

Quantitative degree

Tools

Python

R

Job description

Wholesale Credit Quantitative Research - Analyst

Job Information

• Job Identification 210708980
• Business Unit Commercial & Investment Bank
• Posting Date 02/04/2026, 12:57 PM
• Locations Nirlon Knowledge Park, Western Express Highway, Goregaon (East), Mumbai, IN-MH, 400063, IN
• Job Schedule Full time

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.

Job Description

As a Quantitative Research Wholesale Credit Risk Modeling Analyst within the Wholesale Credit team, you will design, analyze, and deliver quantitative models to support the firm’s Wholesale Credit Stress (CCAR, ICAAP, Risk Appetite) and loan loss reserves models. You will use statistical techniques & tools for building forecasting models. This role will provide you with the opportunity to work with other experienced Wholesale Credit Quantitative Researchers and business partners, enhancing your quantitative as well as business skills.

Job Responsibilities

• Work as a quantitative researcher to design and develop PPNR forecasting models for regulatory purposes.

Minimum Skills, Experience and Qualifications

If you meet the minimum requirements below, you are encouraged to apply to be considered for this role.

• You have a degree in Engineering, Financial Engineering, Computer Science, Mathematics, Sciences, Statistics, Econometrics, or other quantitative fields
• You have a strong background in the following topics – Calculus, Linear Algebra, Probability, and Statistics
• You have solid theoretical and practical knowledge of statistical methods and models: generalized linear models, time-series analysis, clustering, decision trees, logistic regression.
• You are experienced in handling large amount of panel data, and data cleaning/filtering.
• You demonstrate proficiency in at least one of the object-oriented programming languages, and are good at one of Python or R
• Ability to solve problems creatively while working in a dynamic environment. Eagerness to learn about Credit Risk, Risk Parameters, Regulatory and Accounting concepts
• 1-3 years of relevant experience would be preferred.

Additional Skills, Experience and Qualifications

The following additional items would be a plus but not a mandatory requirement.

• Knowledge of Wholesale Credit products and experience in development of loss/PPNR forecasting models for regulatory exercises
• Knowledge of different types of financial products and asset classes, options pricing theory, financial regulations, machine learning , or high-performance computing would be a plus
• Proven ability to develop collaborative relationships with key internal partners to achieve objectives and prioritizations

Beyond that, we are interested in the things that make you unique: personal qualities, outside interests and achievements beyond academia and professions that demonstrate the kind of person you are and the value you could bring to the team.

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 across the world.