Role Overview
Data Scientist Lead supporting Fraud Risk and Monitoring initiatives within a financial services environment. This role focuses on analyzing large datasets, identifying fraud trends, building predictive models, and designing monitoring strategies to mitigate risk and improve business performance.
Key Responsibilities
- Analyze large datasets to identify fraud trends, anomalies, and emerging risk patterns
Design and implement fraud monitoring strategies for new products and capabilities
Optimize fraud detection processes by improving alert logic and reducing false positives
Apply predictive modeling techniques for segmentation, targeting, and risk assessment
Develop and enhance reporting dashboards for fraud and portfolio performance tracking
Establish baselines and track performance against business expectations
Collaborate with risk, product, engineering, and strategy teams
Partner with internal and external data providers ensuring data quality and governance
Support development and enhancement of fraud detection controls and frameworks
Contribute to risk appetite definition and monitoring strategies
Technical Skills
Must Have
- Strong background in Math, Statistics, and Quantitative Analysis
Proficiency in SQL, Python, or R
Strong Analytical Mindset and Data Skills
Experience with Tableau or Power BI
Nice To Have
- Model Development experience
Prior Banking or Financial Services experience
Anti-Fraud / Fraud Analytics experience
Knowledge of Digital Transactions (ACH, Wire Transfer, etc.)
Effective Communication Skills
Soft Skills
- Strong written and verbal communication skills
Strong analytical and problem-solving abilities
Cross-functional collaboration skills
Ability to work in a fast-paced, data-driven environment
Education
- Bachelor s degree (minimum required)