Fraud Strategy Quant Analytics Associate I

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Wilmington, DE
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $165k

$119k most similar roles pay here $211k

This listing doesn't post a salary. Most similar roles pay $128,152–$202,350.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1174 open roles on FindRole.

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At a glance

TL;DR · Fraud Strategy Quant Analytics Associate I

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As a Fraud Strategy Quant Analytics Associate I on the Consumer and Community Banking Fraud Prevention Optimization Strategy team, you will focus on reducing fraud costs while improving customer experience. You will perform complex analyses to identify risk dynamics, trends, and opportunities across the credit card fraud lifecycle. Your daily work involves developing and implementing optimal fraud strategies, identifying key risk indicators, and creating metrics to challenge current business practices. To succeed, you must utilize advanced mathematical techniques and tools like Python, SAS, SQL, AWS, and Snowflake. You will also leverage large language models and machine learning to deliver sustainable improvements. This role requires collaborating with cross-functional partners to solve business challenges and presenting concise data insights to executives while managing the technical complexities of fraud prevention within a banking environment.

Skills

Python SAS SQL AWS Snowflake Machine Learning Large Language Models Natural Language Processing Statistics Mathematics Risk Management

What you'll do

Analyze complex data to identify risk dynamics, trends, and opportunities.
Use advanced mathematical techniques to solve complex business problems.
Develop and implement fraud strategies to reduce losses and improve customer experience.
Identify key risk indicators and develop metrics to enhance reporting.
Translate large amounts of raw data into actionable recommendations for stakeholders.
Present concise analytical findings and performance insights to managers and executives.
Integrate new technologies, such as large language models, to drive business improvements.

What we're looking for

Bachelor's degree in a quantitative field or 3 years of risk management or other quantitative experience.
Background in Engineering, statistics, mathematics, or another quantitative field.
Advanced understanding of Python, SAS, and SQL.
Ability to query large amounts of data and transform them into actionable recommendations.
Strong analytical, problem-solving, and communication skills for interacting with senior executives.
Master's degree in a quantitative field or 2 or more years of risk management or other quantitative experience (preferred).
Hands-on knowledge of AWS and Snowflake (preferred).
Advanced techniques like Machine Learning, LLM Prompting, or Natural Language Processing (preferred).

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