Tech Stack

Description

You will analyze large datasets to detect fraud and abuse, build metrics and models to improve detection, and collaborate with cross-functional teams to shape safety strategy. Your work will protect users and ensure platform integrity.

Requirements

• Bachelor's or Master's degree in Statistics, Computer Science, Mathematics, Economics, or related field
• 5+ years of Data Science experience with large-scale data and statistical analysis
• 1+ year of data science experience in fraud prevention, moderation, or risk
• Proficiency in SQL and Python or R
• Expertise in experimentation and causal inference (A/B testing, cohort analysis)
• Hands-on experience with ML methods (prediction, classification, anomaly detection) in risk or fraud prevention contexts

Responsibilities

• Design and lead analyses and metric evolution for fraud detection
• Develop models, heuristics, and ML solutions for proactive abuse detection
• Evaluate product and policy changes via experimentation (A/B tests, causal inference)
• Own cross-functional partnership with Product, Engineering, Operations, Policy, and Legal
• Build dashboards and reporting frameworks to track platform health and safety