Sr Fraud Data Analyst

Role Overview

The Senior Fraud Data Analyst designs and executes advanced fraud prevention strategies across digital, voice, and card channels. The role uses data mining, SQL querying, and predictive analytics to identify fraud patterns, assess risk, and build proactive solutions.

Responsibilities

• Lead the development, implementation, and optimization of fraud detection strategies using advanced analytics.
• Perform data mining and statistical analysis on large, complex datasets to uncover fraud patterns and anomalies.
• Design and optimize SQL queries for fraud detection workflows.
• Create and present fraud dashboards and reports to senior leadership with actionable insights.
• Collaborate with risk, technology, product, and compliance teams to integrate fraud strategies across the business.
• Conduct root cause analyses of fraud incidents and recommend future-proof solutions.
• Stay current on emerging fraud schemes and regulatory changes.
• Mentor and coach junior analysts.
• Manage relationships with external vendors for fraud detection tools.
• Support fraud investigations while ensuring legal and regulatory compliance.

Requirements

• Bachelor’s degree in finance, economics, data analytics, computer science, or related field (Master’s preferred).
• 5+ years in fraud risk management, fraud detection, or financial crime strategy.
• Advanced SQL skills for complex querying, data manipulation, and performance optimization.
• Expertise in data mining, predictive modeling, and anomaly detection.
• Strong programming skills in Python or R for analysis and machine learning.
• Experience with big data platforms (e.g., Hadoop, Spark) and cloud-based analytics.
• Familiarity with fraud detection technologies including rule-based systems and ML/AI.
• Ability to analyze user behavior data to design low-friction fraud prevention.
• Experience working cross-functionally and managing complex projects.
• Strong communication and presentation skills.
• Knowledge of financial services regulations and fraud management best practices.
• Experience in high-volume, transactional environments.
• Familiarity with fraud detection systems and decision engines.

Nice to Have

• CFE certification preferred.
• Technical certifications (e.g., SQL, Certified Analytics Professional).

Work Model

• Remote, with an in-person onboarding/training component.