Data Scientist - Fraud Analysis

Job Title: Data Scientist - Fraud Analysis

Location: San Francisco, CA / Dallas, TX / Chicago, IL / New York, NY (Hybrid)

Job Summary

• Join the Fraud Analytics team to identify, investigate, and mitigate fraudulent activities using advanced data analytics methodologies.
• Collaborate with cross-functional teams to assess fraud trends, evaluate system performance, develop fraud prevention strategies, and provide actionable insights to leadership.

Key Responsibilities

• Compare outputs from two systems or data sources that are expected to perform similarly, identify discrepancies, and document root causes and threshold impacts.
• Investigate suspicious transactions and determine underlying causes of fraud-related activity.
• Collaborate with machine learning teams and evaluate model performance related to fraud detection.
• Conduct in-depth assessments of evolving fraud trends, including:
  • Merchant Fraud
  • First-Party Fraud
  • Third-Party Fraud
  • Digital Fraud
• Design and implement fraud rules within workflow systems.
• Develop and maintain fraud monitoring reports and dashboards.
• Generate reports and presentations for management outlining risks, incidents, findings, and mitigation strategies.
• Partner with Risk, Operations, and Compliance teams to enhance fraud prevention processes.
• Monitor industry trends, regulatory developments, and fraud prevention best practices to improve detection and mitigation strategies.

Required Skills

• Proven experience in:
  • Fraud Mitigation
  • First-Party Fraud
  • Transactional Fraud
  • Merchant Fraud
  • Digital Fraud Detection
• Strong proficiency in Python.
• Strong SQL skills, including experience working with BigQuery.
• Experience using Jupyter Notebooks.
• Experience with rules management, including reading, comparing, and translating rule logic.
• Knowledge of fraud detection solutions and risk assessment methodologies.
• Familiarity with regulatory compliance standards related to fraud prevention.
• Strong analytical and problem-solving skills.
• Ability to communicate complex data findings through clear and actionable presentations.

Qualifications

• Bachelor's degree in Engineering, Technology, Computer Science, or a related quantitative field.
• 3+ years of dedicated data analytics experience within fraud prevention or risk management.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law.