Fraud Risk Strategy Analyst (Hybrid San Jose, CA)

Experience level: Mid-Senior

Experience required: Up to 2 years

Education: Bachelors degree

Job function: Finance / Risk Analytics

Industry: Financial Services

Employment type: Contract (covering multiple leaves over ~1 year; potential extension based on business need and performance)

Work setup: Hybridcandidate must be based in the San Jose area

Visa sponsorship: Not available

Relocation assistance: No

Openings: 1

Schedule: Day shift, MonFri (Pacific Time)

Overview

Were seeking a talented and dedicated analyst to support a Fraud Risk Strategy team. Youll contribute to projects in fraud detection, risk analysis, and loss mitigation, applying statistics and data science to real-world business challenges in digital payments/e-commerce. This is a hands-on role with high visibility and strong cross-functional collaboration.

Key Responsibilities

• Design rules to detect and mitigate fraud across products and customer segments

• Build Python scripts/models that support fraud strategies and automation

• Investigate novel/large cases and identify root causes and patterns

• Define strategy for different risk types and guide execution

• Partner with Product and Engineering to improve control capabilities

• Develop dashboards/visualizations (Tableau or AWS QuickSight) to track KPIs

• Present insights and recommendations to stakeholders and leadership

Must-Have Qualifications

• Up to 2 years in risk analytics, data analysis, or data science within eCommerce, online payments, user trust/risk/fraud, or abuse investigations

• Bachelors in Data Analytics, Data Science, Mathematics, Statistics, Data Mining, or related field (or equivalent practical experience)

• Demonstrated application of statistics/data science to solve complex business problems

• Proficiency in SQL, Python, and Excel (including core data science libraries)

• Experience working with large datasets

• Proficiency in data visualization (e.g., Tableau; AWS QuickSight a plus)

• Clear communication skills for technical and executive audiences

Nice to Have

• Experience/aptitude solving risk/fraud problems using analytics

• Exposure to AWS, payment rule systems, fraud investigations, working with ML teams, and knowledge of fraud typologies

Expected Outcomes (612 Months)

• Design and implement data-driven fraud strategies and rules to address emerging trends while protecting customer experience

• Build dashboards/visualizations to track strategy KPIs

• Collaborate with Product/Engineering to deploy real-time, scalable fraud solutions

• Deliver persuasive, data-backed presentations and recommendations to leadership

  Interview Process

• Multiple Zoom interviews (23)

• SQL assessment during the first interview

• Strictly contract role (covering multiple leaves over ~1 year)