About this role

Collaborate with data scientists, fraud strategists, and business stakeholders to support and enhance real-time fraud detection strategies.
Analyze complex datasets to detect patterns and trends related to account takeover and scam-related fraud.
Use Python, SQL, and other analytical tools to extract actionable insights from large volumes of data.
Evaluate and optimize vendor and internal tools to improve detection of fraudulent behaviors across digital experiences.
Support anomaly detection efforts to identify organized fraud rings and coordinated attacks.
Communicate findings clearly to influence stakeholders and guide fraud prevention strategies.
Partner with cross-functional teams to develop and refine fraud detection models, dashboards, and reporting tools.
Contribute to the continuous improvement of fraud analytics capabilities and operational effectiveness.

7+ years of experience in data analytics, preferably within fraud detection, risk management, or cybersecurity.
Strong proficiency in Python and SQL for data analysis and automation.
Experience working with large-scale datasets and modern data platforms.
Skilled in using analytics tools for statistical analysis, visualization, and reporting.
Familiarity with fraud detection methodologies, especially related to account compromise and scams.
Ability to translate complex data into clear, actionable insights for technical and non-technical audiences.
Strong communication and collaboration skills to work effectively across teams.
Experience in anomaly detection or behavioral analytics is a plus.

Senior Manager, Fraud Detection and Analytics

Key skills