Data Science Manager - Fraud

📋 Description

• Set a 6-12-month roadmap with Product, Engineering, and GTM, and assign priorities and
• Define product metrics, their underlying data, and reporting and alerting practices; use the
• Establish a repeatable process for customer retrospectives and proofs of concept, including data
• Identify fraud signals and product opportunities across analyses and work with Product and MLEs to
• Review analytical designs, data models, code, and model evaluations; contribute to investigations
• Coach and develop data scientists through feedback and growth opportunities

🎯 Requirements

• Proven experience managing and mentoring high-performing data scientists
• Deep domain expertise in fraud, risk, or related areas
• Strong experience in product analytics, metric design, and measuring product performance
• Hands-on experience in Python, SQL, and statistical modeling
• Excellent communication cross-functional collaboration skills across Product, Engineering, ML, GTM
• Experience partnering with customers to deliver data-driven insights and solutions