Analyst, Fraud Detection and Analytics

Fidelity Investments•Jersey City, NJ

19h•$83,000 - $158,000•Onsite

About The Position

This role involves working closely with data scientists, fraud strategists, and business stakeholders to support real-time fraud detection and prevention strategies. The analyst will apply analytical techniques to large-scale datasets, utilize vendor tools to detect and mitigate scam events where customers are manipulated into sending money to legitimate payees. Additionally, the role contributes to the broader Detection and Analytics group to define processes and optimize overall detection strategy, including the detection of Account Take Over events, Identity Theft, and other types of fraud.

Requirements

Strong blend of advanced analytics expertise, fraud-domain knowledge, and cross-functional communication skills.
Hands-on experience using Python, SQL, and analytical platforms to work with large, complex datasets.
Ability to uncover actionable insights.
Adept at identifying scam-related fraud patterns.
Experience supporting anomaly detection efforts.
Experience contributing to the detection of coordinated fraud attacks and organized fraud rings.
Experience leveraging both vendor products and internally built solutions.
Ability to translate complex analytical findings into clear, influential insights.
Strong collaboration and communication skills.

Responsibilities

Support real-time fraud detection and prevention strategies.
Apply analytical techniques to large-scale datasets.
Utilize vendor tools to detect and mitigate scam events.
Work with the broader Detection and Analytics group to define processes and optimize overall detection strategy.
Detect Account Take Over events, Identity Theft, and other types of fraud.
Enhance customer authentication and identify risk indicators within authenticated sessions.
Develop and refine fraud detection models and dashboards.
Apply identity proofing tools and fraud-mitigation methodologies.
Translate complex analytical findings into clear, influential insights.
Drive product changes and data-informed decision-making across business units.
Partner with stakeholders to advance strategies that reduce scam risk and enhance fraud-detection capabilities.