Quantitative Analytics Associate, Fraud Prevention Optimization Strategy

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Wilmington, DE
Posted: 99 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $170k

$130k most similar roles pay here $210k

This listing doesn't post a salary. Most similar roles pay $137,775–$202,050.

Based on 240 similar postings.

Employer

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 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Quantitative Analytics Associate, Fraud Prevention Optimization Strategy

Role Posting Log in to save

As a Quantitative Analytics Associate - Fraud Prevention Optimization Strategy, you will join the Consumer and Community Banking team to reduce fraud costs while improving customer experience. You will perform complex analyses to identify risk dynamics, trends, and opportunities within the credit card fraud lifecycle. Your daily responsibilities include developing optimal fraud strategies, identifying key risk indicators, enhancing reporting, and presenting concise data insights to cross-functional partners and executives. To succeed, you must utilize advanced mathematical techniques and tools including Python, SAS, SQL, AWS, and Snowflake. You will also champion the use of large language models and machine learning to drive business improvements. The role focuses on solving complex problems by transforming large datasets into actionable recommendations to mitigate losses and optimize business processes within the fraud prevention domain.

Skills

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

What you'll do

Analyze complex data to identify risk dynamics, trends, and opportunities for fraud prevention.
Use advanced mathematical and analytical techniques to solve complex business problems.
Develop and implement optimal fraud strategies to reduce losses and improve customer experience.
Identify key risk indicators and develop metrics to enhance reporting and challenge current practices.
Translate large datasets into actionable recommendations for business partners and leadership.
Present complex analysis succinctly to managers and executive stakeholders.
Leverage new technologies, including Large Language Models, to drive scalable business improvements.

What we're looking for

Bachelor’s degree in a quantitative field or 3 years of risk management or other quantitative experience.
Master's degree in a quantitative field or 4 or more years of risk management or other quantitative experience.
Background in Engineering, statistics, mathematics, or another quantitative field.
Advanced understanding of Python, SAS, and SQL.
Experience delivering recommendations to leadership and communicating with senior executives.
Ability to query large amounts of data and transform it into actionable recommendations.
Knowledge of AWS and Snowflake is preferred.
Proficiency in advanced techniques like Machine Learning, LLM Prompting, or Natural Language Processing is an advantage.

Save