Data Analyst III - Fraud

Fanatics•Denver, CO

5h•$116,000 - $145,000

About The Position

As a Senior Fraud Data Analyst III at Fanatics Betting & Gaming, you will be a core driver of our fraud analytics and data infrastructure. This role is highly hands-on and execution-focused, with a mandate to fully automate and scale fraud reporting and analysis currently operating in Google Sheets into a robust, production-grade data pipeline. You will sit at the intersection of Fraud & Risk, Data Engineering, and Analytics, owning fraud datasets end-to-end—from raw ingestion and modeling through insight generation and decision support. This is a senior, high-impact role for someone who can work independently, identify gaps, and drive initiatives to completion without heavy oversight. The ideal candidate is a SQL and dbt expert, deeply fluent in modern analytics engineering practices, and brings strong domain expertise in fraud detection, prevention, and investigation within regulated, high-volume environments.

Requirements

5+ years of experience in analytics, data analysis, or analytics engineering, with significant focus on fraud, risk, or payments.
Expert-level SQL skills with experience working in cloud data warehouses (Snowflake, BigQuery, Redshift).
Strong experience with dbt and modern analytics engineering best practices.
Proven ability to take ambiguous, manual processes and turn them into clean, automated, scalable solutions.
Experience working independently and owning projects end-to-end.
Strong analytical judgment and ability to communicate findings clearly to both technical and non-technical stakeholders.

Nice To Haves

Direct experience in fraud detection, payments risk, or financial crime within sports betting, gaming, fintech, or ecommerce.
Familiarity with: Chargeback workflows and card networks KYC/AML processes Fraud tooling or risk engines
Experience with BI tools such as Tableau, Sigma, or similar.

Responsibilities

Fraud Data Pipeline Ownership & Automation Lead the migration of fraud reporting and workflows into a fully automated, scalable data pipeline.
Design, build, and maintain analytics-ready data models using dbt that support fraud monitoring, investigation, and strategy.
Partner with Data Engineering to ensure reliable ingestion, data quality, and documentation of fraud-related datasets.
Fraud Analytics & Monitoring Develop and maintain dashboards and reporting that track key fraud metrics such as: Fraud rates and loss Chargebacks and disputes Bonus abuse, promo abuse, and multi-accounting KYC and account integrity signals Surface emerging fraud patterns and anomalies through proactive analysis.
Advanced SQL & Analytics Engineering Write performant, production-quality SQL across large, complex datasets.
Build modular, reusable dbt models that enable self-service analytics for Fraud & Risk teams.
Implement testing, freshness checks, and documentation to ensure trust in fraud data.
Cross-Functional Partnership Work closely with Fraud & Risk, Payments, Customer Support, Product, and Engineering to align on definitions, metrics, and investigative workflows.
Translate fraud questions and operational needs into clear analytical outputs and recommendations.
Strategic Insight & Decision Support Provide actionable insights to fraud leadership to inform: Risk rules and thresholds Tooling and vendor evaluations Process improvements and operational tradeoffs