Experience Level: Mid-Senior

Experience Required: Up to 2 years

Education: Bachelor’s degree

Job Function: Finance / Risk Analytics

Industry: Financial Services

Employment Type: Contract (covering multiple leaves over ~1 year; potential to extend based on business needs and performance)

Work Setup: Hybrid — must be based in the San Jose area

Visa Sponsorship: Not available

Relocation Assistance: No

Schedule: Mon–Fri, Day Shift (Pacific Time)

Overview

We’re looking for a talented, detail-oriented analyst to support the Fraud Risk Strategy team. You’ll contribute to projects in fraud detection, risk analysis, and loss mitigation, using statistics and data science to solve real-world challenges in digital payments and eCommerce. This hands-on role involves high collaboration with cross-functional teams and significant business impact.

Key Responsibilities

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

• Develop Python scripts and models that enhance fraud detection and automation

• Investigate complex or high-impact fraud cases and identify root causes

• Define and execute strategies for multiple risk types

• Collaborate with Product and Engineering teams to improve control systems

• Build dashboards and 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, or user trust/fraud domains

• Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, or related field (or equivalent experience)

• Proficiency in SQL, Python, and Excel, including key data science libraries

• Experience working with large datasets

• Skilled in data visualization using Tableau (AWS QuickSight a plus)

• Strong analytical and communication skills, with the ability to explain results to technical and non-technical teams

Nice to Have

• Experience solving risk or fraud problems using analytics

• Familiarity with AWS, payment rule systems, and machine learning workflows

• Understanding of fraud investigations and typologies

Expected Outcomes (6–12 Months)

• Design and implement data-driven fraud strategies to reduce loss and improve customer experience

• Develop dashboards to monitor key fraud metrics and performance indicators

• Partner with teams to deploy scalable, real-time fraud detection solutions

• Deliver actionable insights and recommendations that influence business decisions

Interview Process

• Two to three Zoom interviews

• SQL skills assessment during the first interview

• Contract position covering multiple leaves (approx. 12 months)