
Quant Analytics Associate
at J.P. Morgan
Posted a month ago
No clicks
- Compensation
- Not specified
- City
- Mumbai
- Country
- India
Currency: Not specified
Join the Fraud Prevention Optimization team to reduce fraud losses and improve customer experience through advanced analytics and strategic decisioning. You will analyze complex data, build and implement fraud strategies across the credit card lifecycle, and deliver actionable insights to business partners and senior leaders. The role emphasizes Python, SAS, SQL, machine learning and new tools like large language models, and requires close collaboration with cross-functional teams.
Location: Mumbai, Maharashtra, India
Join our dynamic team as a Quantitative Analytics Associate in the Consumer and Community Banking Fraud Prevention Optimization Strategy team. You'll play a key role in reducing fraud costs and enhancing customer experience through complex analyses and collaboration. This position offers growth opportunities and the chance to work with cross-functional partners, presenting insights to managers and executives. Be part of a team that leverages advanced analytics and innovative tools to promote impactful business improvements.
Job Summary
As a member of the Fraud Prevention Optimization team, you will focus on reducing cost of fraud, through complex analyses combined with business insights and collaboration. Our objective is reducing losses and / or operating expenses while balancing customer impact through optimizing business processes and decisioning. Team members will frequently interact and communicate with cross-functional partners and present complex analysis succinctly to managers and executives. This role provides an opportunity to be part of a dynamic team that is instrumental in protecting the bank by leveraging complex analytics and new tools like large language models to deliver sustainable, hard hitting business improvements.
Job Responsibilities
- Interpret and analyze complex data to formulate problem statement, provide concise conclusions regarding underlying risk dynamics, trends, and opportunities.
- Use advanced analytical & mathematical techniques to solve complex business problems.
- Manage, develop, communicate, and implement optimal fraud strategies to reduce fraud related losses and improve customer experience across credit card fraud lifecycle.
- Identify key risk indicators, develop key metrics, enhance reporting, and identify new areas of analytic focus to constantly challenge current business practices.
- Provide key data insights and performance to business partners.
- Collaborate with cross-functional partners to solve key business challenges.
- Assist team efforts in the critical projects while providing clear/concise oral and written communication across various functions and levels.
- Champion the usage of latest technology and tools, such as large language models, to drive value at scale across business organizations.
Required qualifications, capabilities, and skills
- Bachelor’s degree in a quantitative field or 3 years risk management or other quantitative experience
- Background in Engineering, statistics, mathematics, or another quantitative field
- Advanced understanding of Python, SAS, and SQL
- Query large amounts of data and transform into actionable recommendations.
- Strong analytical and problem-solving abilities
- Experience delivering recommendations to leadership.
- Self-starter with ability to execute quickly and effectively.
- Strong communication and interpersonal skills with ability to interact with individuals across departments/functions and with senior level executives
Preferred qualifications, capabilities, and skills
- MS degree in a quantitative field or 2 or more years risk management or other quantitative experience.
- Hands on Knowledge of AWS and Snowflake.
- Advanced analytical techniques like Machine Learning, Large Language Model Prompting or Natural Language Processing will be an added advantage.




