Senior Data Modeler, Fraud Risk Detection

Role overview

A senior-level data modeling role within an analytics function that supports fraud risk detection for financial services use cases. The work centers on designing, validating, and maintaining models that surface suspicious or high-risk activity. The position is remote within the United States with San Diego, California listed as the reference office, and operates on a full-time day-shift schedule.

Responsibilities

- Design, build, and refine data models that drive fraud risk detection across financial services datasets - Apply quantitative and statistical methods to identify patterns associated with fraudulent or high-risk behavior - Document modeling approaches, assumptions, inputs, and performance outcomes for downstream consumers - Collaborate with analytics, risk, and engineering partners to translate model outputs into operational workflows - Monitor deployed models for stability and accuracy, iterating as new data and fraud patterns emerge

Requirements

- Demonstrated senior-level experience in data modeling, analytics, or a related quantitative discipline - Hands-on background with fraud, risk, or anomaly detection problems, ideally in a financial services setting - Strong proficiency in SQL and statistical or machine learning techniques applied to large datasets - Ability to clearly communicate methodology, limitations, and results to both technical and non-technical audiences

Benefits and work setup

- Remote-first position within the United States, with San Diego, California as the listed reference work location - Full-time schedule on day shift hours - Salary range: $82,644 - $143,249 - 15 days of flexible time off per year - Regular full-time employment status within the Analytics department