Quant Analytics Senior Associate

JPMorgan Chase & Co.•Plano, TX

About The Position

As a Quant Analytics Senior Associate within the Fraud Strategy team, you will play a critical role in identifying and mitigating fraud risks, leveraging your analytical expertise to promote impactful strategies and deliver end-to-end solutions.

Requirements

Bachelor’s degree in finance, economics, statistics, or a quantitative field.
Minimum 3 years of experience in Fraud Strategy, analytics, or a quantitative discipline.
Strong background in statistics, econometrics, or related quantitative methodologies.
Advanced proficiency in SAS, SQL, and spreadsheet tools; ability to query and manipulate large datasets to generate actionable insights.
Demonstrated ability to drive complex projects independently, managing multiple priorities and delivering results.
Strong analytical and problem-solving skills, with a keen attention to detail.
Excellent written and verbal communication skills; proven ability to present complex analyses and recommendations to management and stakeholders.

Nice To Haves

Master’s degree in a quantitative field.
At least 1 year of experience in Risk Management, Fraud Strategy, or analytics within financial services.

Responsibilities

Develop, maintain, and enhance analytics to provide management with comprehensive insights into fraud trends and account quality.
Analyze key performance metrics and profitability drivers across the full account lifecycle, delivering actionable recommendations to inform strategy and operational decisions.
Gain a deep understanding of operational processes (e.g., underwriting, portfolio management, collections) to identify and address fraud risk drivers.
Lead and execute complex projects independently, from initial analysis through implementation and performance monitoring.
Conduct ad hoc analytics and contribute to cross-functional initiatives, representing the Fraud Strategy team in collaborative efforts.
Communicate findings and recommendations clearly to stakeholders at all levels, supporting data-driven decision making.