Fraud Data Analyst

Job Title: Fraud Data AnalystCompany: Big Four ClientLocation: Bay Area (CA)Work Authorization: U. S. Citizen or Green Card HolderPay Rate: $85-$95 per hour (W2); Max of $110 per hour (Corp-to-Corp)Duration: 7+ MonthsOverviewWe are seeking an experienced Fraud Data Analyst specializing in gift card fraud to join our team in the Bay Area. In this critical role, you will leverage your advanced PySpark expertise (6–9 years) and strong analytical skills to develop and implement robust fraud monitoring solutions that protect our customer's business.

You will work cross-functionally with Fraud, Legal, Operations, Product, and Business Development teams to proactively detect, analyze, and mitigate complex gift card fraud schemes. Key ResponsibilitiesCollaborate with cross-functional teams including Fraud, Legal, Operations, Product, and Business Development to design and implement scalable fraud monitoring solutions and dynamic fraud prevention strategies. Analyze large-scale transactional and behavioral datasets using advanced PySpark to uncover trends, patterns, and emerging anomalies related to gift card fraud. Develop and maintain insightful dashboards and regular reports to monitor suspicious activity trends and fraudulent behaviors.

Create and track fraud-specific Key Performance Indicators (KPIs) to measure and optimize the effectiveness of fraud prevention initiatives. Proactively identify and assess new and emerging gift card fraud schemes, recommending and executing risk mitigation strategies. Partner with other fraud analysts, data scientists, and engineers to build and refine fraud prevention tools, machine learning models, and monitoring systems. Communicate analytical findings and recommendations clearly to both technical and non-technical stakeholders. Required Qualifications: Advanced-level proficiency in PySpark (6–9 years of hands-on experience), including large-scale data processing and ETL workflows. Demonstrated experience in fraud detection, ideally with a focus on gift card fraud.

Strong skills in data analysis, pattern recognition, and statistical modeling. Professional experience collaborating with cross-functional business and technical teams. Excellent written and verbal communication skills. Preferred Qualifications: Proficiency in SQL and Hadoop for data extraction, manipulation, and analytics. Experience developing dashboards and reports using BI tools (e. g. , Tableau, PowerBI). Familiarity with building or evaluating machine learning models for fraud detection.