Manager – FWA Data Science

About the role

The FWA Data Science Manager leads the transformation of validated fraud, waste, and abuse (FWA) analytical prototypes into production‑ready detection models. Working closely with Actuarial, Claims Integrity, and AI Engineering teams, the role ensures models stay effective against evolving fraud patterns.

Key responsibilities

• Assess and industrialise AI/ML prototypes, refining logic, enhancing statistical rigor and feature engineering.
• Develop, enhance and retrain detection models, building advanced fraud features, risk scoring and anomaly detection.
• Define success metrics, monitor precision/recall, conduct false‑positive/negative analysis and support production readiness reviews.
• Analyse investigation outcomes to identify emerging fraud behaviours, design new detection features and advise model updates.
• Continuously monitor deployed models, recommend retraining or recalibration, and maintain documentation and governance artifacts.

Required profile

• Bachelor’s degree in Computer Science, Data Science, AI or a related field.
• Experience in health‑insurance claims analytics, fraud analytics or risk management.
• Proven ability to work cross‑functionally with actuarial, engineering and operations teams.

Required skills

• Python
• SQL
• SAS
• Machine Learning
• Statistical Analysis
• Feature Engineering
• Model Validation & Performance Analysis
• Fraud Analytics (FWA)
• Healthcare Claims Analytics
• NLP & LLM Applications
• Google Cloud Platform (GCP)
• Cloud‑Based Analytics Solutions
• Power BI / Data Visualization