Senior Fraud Detection Analyst

Fidelity Investments • Durham, NC

7d • Onsite

About The Position

In this role, you will work closely with data scientists, fraud strategists, and business stakeholders to support real-time fraud detection and prevention strategies. Your work will focus on identifying payment card fraud schemes and implementing detection solutions to mitigate risk, using advanced analytics and data analysis tools. The Fraud Detection Analytics Team is responsible for ensuring that fraudulent events—such as account logins, account openings, and payment attempts—occurring on Fidelity’s platform are detected and mitigated in a timely manner. The team leverages a combination of vendor and internally developed tools and models to enable real-time detection and interdiction at various stages of the customer lifecycle. Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Requirements

• Bachelor's with 5 plus years or Master's with 3 plus years of experience in data analytics, preferably in fraud detection, cybersecurity, or risk domains.
• Strong proficiency in Python and SQL for data analysis and automation.
• Experience working with large-scale datasets and analytical platforms.
• Skilled in using analytics tools (e.g., dashboards, statistical packages, data visualization platforms) to perform advanced analytics and uncover actionable insights.
• Familiarity with payment card fraud detection and risk management.
• Ability to translate complex data into clear, actionable insights.
• Strong communication and collaboration skills to work across teams and influence decisions.

Nice To Haves

• Experience in anomaly detection or fraud analytics is a plus.

Responsibilities

• Analyze complex datasets to identify risk signals related to fraudulent debit card transactions.
• Use Python, SQL, and analytical tools to analyze large, complex datasets and extract actionable insights.
• Implement fraud detection strategies in a real-time fraud decisioning engine.
• Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings.
• Communicate insights clearly and effectively to influence stakeholders and drive product changes.
• Collaborate across business units to drive data-informed strategies for fraud detection.
• Contribute to the continuous improvement of the fraud detection program, through rule and model refinement, fraud hunting, and data discovery.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior