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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Science Manager - **Company:** Plaid's Network - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Data Transformation, Programming Tools, Python (Programming Language), Machine Learning, Software Tools, SQL Databases, Usage Analysis, Scripting - **Published:** September 16, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-science-manager-fraud-san-francisco-ca--0216d272-b163-49c7-8485-f7916fe76ddb ## About the Role * Proven experience managing, mentoring, and developing high-performing data scientists. * Deep domain expertise in fraud, risk, or related areas. * Strong experience in product analytics, metric design, and measuring product performance. * Experience partnering directly with customers to deliver data-driven insights and solutions. * Strong technical depth in Python, SQL, statistics, product analytics, and applied modeling. * Demonstrated ability to set technical direction and deliver complex, high-impact initiatives through a team while remaining hands-on. * Excellent communication and cross-functional collaboration skills across Product, Engineering, Machine Learning, GTM, and customer stakeholders. Nice-to-Have: * Experience working with graph-based data or systems to identify fraud patterns and improve model performance. * Experience applying causal inference techniques to complex product or risk problems. * Experience using model interpretability techniques across both traditional machine learning and modern model architectures. * Experience with dbt or similar data transformation and analytics engineering tools., Analysis Skills, Artificial Intelligence (AI), Coaching, Communication Skills, Compensation and Benefits, Cross-Functional, Customer Relations, Customer/Client Research, Data Analysis, Data Modeling, Data Science, Diversity, Ecosystems, Fortune 500 Customers, Machine Learning, Mentoring, Metrics, Performance Management, Performance Modeling, Product Design, Product Documentation, Product Engineering, Product Planning, Programming Tools, Proof of Concept, Python Programming/Scripting Language, Risk, SQL (Structured Query Language), Statistics, Team Building, Team Lead/Manager, Team Player, Technical Delivery ## Description As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the teams roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: * Set a 6-12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. * Define product metrics, their underlying data, and reporting and alerting practices; use the results in roadmap and investment decisions. * Establish a repeatable process for customer retrospectives and proofs of concept, including data checks, evaluation methods, and clear recommendations. * Identify fraud signals and product opportunities that recur across customer analyses and work with Product and MLEs to develop them. * Review analytical designs, data models, code, and model evaluations; contribute directly to investigations where your expertise is needed. * Coach data scientists through clear expectations, regular feedback, performance discussions, and growth opportunities. * Use AI-assisted analysis and development tools where useful, and ensure results are properly reviewed before informing customer recommendations or product decisions. Responsibilities: * Define how Plaid measures, evaluates, and improves the performance of its Fraud products. * Apply fraud expertise, product analytics, and customer-facing data science to drive end-to-end product and business impact. * Translate customer insights and fraud analyses into scalable product capabilities and opportunities for GTM growth. * Lead and develop a high-performing team while remaining technically hands-on with critical analyses and initiatives. * Raise the bar for product metrics, analytical rigor, and the data foundations that power decision-making across Fraud. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [JavaScript? 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