Fraud Analytics Senior Analyst

About the Company:

Our client is a fast-growing financial technology company providing credit and financial wellness products across the consumer and lending ecosystem. The organization leverages data, analytics, and modern technology to expand responsible access to credit and improve customer experience.

The Senior Fraud Analytics Analyst will play a key role in detecting, preventing, and mitigating fraud across the company’s financial products. This individual will leverage data-driven insights, advanced analytics, and modeling to identify patterns of suspicious behavior and implement effective fraud prevention strategies. The role requires close partnership with risk, operations, compliance, and technology teams to develop scalable solutions that protect both customers and the business.

• Design, implement, and refine fraud detection models, rules, and monitoring systems across multiple products and channels.
• Conduct deep-dive analytics to identify emerging fraud patterns, trends, and vulnerabilities.
• Build dashboards, reports, and performance metrics to track fraud losses, detection rates, and operational effectiveness.
• Partner with data engineering and product teams to improve data pipelines, signal quality, and alert response times.
• Collaborate with risk and operations to translate analytics into actionable controls, case triage workflows, and policy updates.
• Use experimentation and model validation to improve detection accuracy and minimize false positives.
• Stay informed on new fraud tactics, regulatory changes, and best practices in digital fraud prevention.
• Mentor junior analysts and contribute to the continued development of the fraud analytics function.

• Bachelor’s degree in Statistics, Mathematics, Data Science, Economics, or a related field.
• 5+ years of experience in fraud analytics, credit risk, or related analytical roles within financial services or fintech.
• Proficiency in SQL for data manipulation and analysis; strong experience in Python or R for modeling.
• Demonstrated experience building and maintaining fraud detection models or rules-based systems.
• Solid understanding of key fraud concepts (application fraud, synthetic identities, chargebacks, transaction monitoring).
• Strong communication skills with the ability to explain technical findings to non-technical stakeholders.

• Familiarity with fraud prevention platforms, third-party data providers, or digital identity solutions.
• Experience in lending, payments, or consumer credit environments.
• Knowledge of big data and cloud analytics tools (e.g., AWS, GCP, Snowflake, Spark).
• Experience mentoring junior analysts or leading small project teams.

• Opportunity to shape the fraud analytics strategy within a growing fintech organization.
• Competitive compensation and benefits package.
• Exposure to advanced data environments and cross-functional collaboration.
• Supportive culture focused on innovation, analytics, and continuous learning.