Data Scientist – Fraud Detection & Risk Analytics

New York, NY | Hybrid | Full-time

About the Company

My client is redefining how fraud is detected in the P&C insurance space. Our data-science-driven platform connects insights across employers, insurers, and contractors to prevent workers’ compensation and personal injury fraud, saving millions in losses across blue-collar industries.

We’re now looking for a Data Scientist to join our growing team and help build smarter, more predictive systems that transform the future of fraud detection.

What You’ll Do

As a Data Scientist, you’ll work at the intersection of data, engineering, and real-world impact designing and deploying models that detect fraudulent activity and assess labour risk.

You’ll collaborate closely with product and engineering teams to bring data-driven intelligence into production and shape the next generation of our analytics platform.

Key Responsibilities

Design, test, and deploy machine learning models to identify fraudulent patterns
Analyze large-scale datasets to extract actionable insights for internal and client-facing use
Partner with engineering and leadership to align models with business goals
Continuously refine models and monitor performance in production

What We’re Looking For

Technical Skills

Strong proficiency in Python for data analysis, modeling, and ML workflows
Experience with SQL and relational databases (PostgreSQL preferred)
Familiarity with AWS or other cloud platforms
Strong grasp of experimentation, model evaluation, and data validation

Soft Skills

Self-starter with a problem-solving mindset
Excellent communicator who can translate data into decisions
Thrives in a fast-paced, early-stage environment

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