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Data Science Manager - Fraud

Plaid · New York City Office

hybridsenior$216,000–$329,400Posted Sep 12, 2026PythonSQLMachine LearningProduct AnalyticsStatistics

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About this role

**Data Science Manager - Fraud** **About the Role** Lead a team of data scientists within Plaid's Fraud Data organization, focusing on customer-facing data science and fraud product analytics. You'll set team roadmaps, develop talent, and remain hands-on with critical analyses and technical reviews. **Key Responsibilities** • Set 6-12 month roadmaps with Product, Engineering, and GTM teams • Define product metrics, data foundations, and reporting/alerting practices • Establish repeatable processes for customer retrospectives and proofs of concept • Identify fraud signals and product opportunities from customer analyses • Review analytical designs, data models, code, and model evaluations • Coach and develop high-performing data scientists • Translate customer insights into scalable product capabilities **Required Qualifications** • Proven experience managing and developing high-performing data scientists • Deep domain expertise in fraud, risk, or related areas • Strong product analytics and metric design experience • Direct customer partnership experience delivering data-driven insights • Technical proficiency: Python, SQL, statistics, product analytics, applied modeling • Ability to set technical direction and deliver complex initiatives through a team • Excellent cross-functional communication skills **Nice-to-Have** • Graph-based data/systems experience for fraud pattern identification • Causal inference techniques applied to product/risk problems • Model interpretability techniques across ML architectures • dbt or similar data transformation tools **About Plaid** Plaid powers financial connectivity for millions of users across 12,000+ financial institutions in the US, Canada, UK, and Europe. We're building tools that empower developers and improve how people interact with their finances. *Equal opportunity employer committed to diversity and reasonable accommodations.*

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