Fraud Abuse Specialist, Digital Fraud & Abuse

Why Join GEICO?

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.

Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge:
Great Company, Great Culture, Great Rewards, and Great Careers.

Like all large digital enterprises, GEICO faces industry‑wide challenges related to digital fraud and customer account abuse. These challenges present an opportunity to strengthen customer trust, improve resilience across our digital experiences, and lead with thoughtful, modern protections. By establishing a dedicated Digital Fraud & Abuse capability, GEICO is taking a proactive, coordinated approach - owning the customer abuse lifecycle end to end and continuously improving the effectiveness of the controls that safeguard our customers and our business.

This individual contributor position is seeking a Fraud Abuse Specialist to help develop fraud analytics models that detect suspicious activity throughout GEICO's business sector or use industry experience to create systematic solutions for persistent challenges. You'll apply advanced data analysis skills-including SQL, Python, machine learning, and data science-to drive critical, high-impact projects by collaborating with engineers, product teams, and business stakeholders in the digital fraud domain.

In this role, you will play an important part in standardizing processes that enable smart decision-making, helping us respond quickly to emerging threats.

This role will:

* Develop and maintain advanced fraud models to identify identity fraud, account takeover, and synthetic identity risks.

* Perform risk analyses and manage complex data sets using tools such as SQL, Python, and R.

* Monitor fraud analytics encompassing Identity and Entity Resolution/Detection, Social Network Analysis, and Unsupervised Monitoring techniques.

* Establish anomaly behaviors and indicators, both within and outside defined ranges, that prompt active response.

* Integrate data from third-party technology providers and tools to continuously enhance fraud detection capabilities.

* Oversee the ongoing performance of fraud analytic models to ensure effectiveness as fraud schemes evolve.

* Assist in developing dashboards to report key performance indicators and generate suspicious activity alerts for the operations team.

* Conduct comprehensive fraud risk assessments to identify program vulnerabilities, evaluate risks, set tolerances, and recommend mitigation strategies.

* Establish and report on Key Performance Indicators, including alert volume, adjudication outcomes, time to resolution, fraud type, and entry point.

* Demonstrate proficiency in data visualization and dynamic dashboard creation using Tableau.

* Possess experience with both relational and non-relational database systems and architecture.

* Exhibit a strong passion for problem identification and solution optimization.

* Maintain meticulous attention to detail along with excellent verbal, written, analytical, and organizational skills.

* Leverage data and technical expertise to discover innovative approaches to scaling signal analysis and identifying fraudulent actors.

* Manage the complete lifecycle of complex issues, from identification through scalable solution implementation.

* Utilize agentic AI systems to automate workflows, enhance pattern detection, and expedite investigation and detection initiatives.

Qualifications

Required

* Bachelor's degree in Math, Statistics, Computer Science, or related Science field, or experience in data science, machine learning or data mining.

* 5+ years of relevant analytic experience in within digital fraud, abuse prevention, identity risk, and related fields.

* Demonstrated strong technical…