Lead Enterprise Fraud Risk Analyst

Located in DC, NYC, Philadelphia, or Wilmington

The Lead Enterprise Fraud Risk Analyst is responsible for executing advanced data analytics to identify, analyze, and mitigate internal and external fraud risks. This role will conduct investigative analyses, generate insights on emerging fraud patterns, and partner with cross‑functional teams to improve fraud detection, prevention, and reporting. This role will also execute fraud incident management activities and assist with development and documentation of incident management processes to mature Amtrak’s fraud risk management program.

The Analyst is a member of the Fraud Risk Management Team and is expected to lead preliminary investigations which may be referred to other investigative teams.

This position supports Amtrak's Enterprise Fraud Risk Management Program and is responsible for identifying, analyzing, and investigating a broad range of fraud risks across the organization, including procurement fraud, financial statement fraud, bribery and corruption, payment card fraud, and other internal and external fraud schemes. The ideal candidate brings broad fraud analytics and investigative experience across multiple fraud domains, rather than expertise in a single specialty such as AML, financial crimes, or cybersecurity.

Bachelor’s Degree or equivalent combination of education, training and/or relevant experience. Plus 6 years of relevant work experience.

Minimum 3 years of hands‑on experience in an advanced analytical role using Data Science or Machine Learning.

• Bachelor’s Degree or equivalent combination of education, training and/or relevant experience. Plus 8 years of relevant work experience.
• Degree in Computer Science, Mathematics, Finance, or a related field.
• Practical, hands‑on experience applying AI/ML techniques

• Advanced proficiency in SQL and demonstrated ability to work with large complex datasets.
• Strong analytical and problem‑solving skills, with the ability to relate multiple datasets from complex business processes, simplify and transform them into meaningful features, ready to be consumed in predictive models.
• Demonstrated experience in data visualization tools such as Tableau, Power BI, or similar.
• Fraud expertise, including knowledge of common fraud schemes, risk indicators, control weaknesses, and industry best practices for detection and prevention.
• Previous experience investigating large, complex datasets, with the ability to identify anomalies, connect disparate data points, perform root cause analysis, and develop actionable insights.
• Excellent oral and written communication skills, with the ability to translate complex technical concepts for endusers while engaging deeply with technical investigative teams.
• Ability to work independently and collaboratively in a fast‑paced, dynamic environment.
• Preferred proficiency in Python or R for data manipulation, modeling, and automation.
• Preferred previous experience with Payment Card Fraud schemes and detection methods.
• Preferred familiarity with calculating and communicating metrics for management reporting.
• Preferred familiarity with risk management frameworks.