Data Science Manager Fraud
Plaid is a financial data network and fintech infrastructure company that helps people securely connect financial accounts to digital financial services.
Maintainer signals as of 9/2/2026
Funding history
Projects
About Plaid Inc.
Plaid provides developer infrastructure and financial tools for account connectivity, financial data access, bank payments, identity verification, AML monitoring, credit and underwriting, and fraud prevention. Its network supports thousands of fintech companies and more than 12,000 financial institutions across the United States, Canada, the United Kingdom, and Europe.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead customer-facing data science and fraud product analytics. You will set the team's roadmap, define metrics and reporting practices, establish customer-analysis processes, identify product opportunities, review analytical work, investigate critical issues, and coach data scientists.
Requirements
- Experience managing, mentoring, and developing data scientists.
- Deep expertise in fraud, risk, or related domains.
- Experience in product analytics, metric design, and measuring product performance.
- Experience partnering directly with customers on data-driven insights and solutions.
- Technical depth in Python, SQL, statistics, product analytics, and applied modeling.
- Ability to set technical direction and deliver complex initiatives through a team while remaining hands-on.
- Communication and cross-functional collaboration skills.
Responsibilities
- Set a 6–12-month roadmap with Product, Engineering, and GTM.
- Define product metrics, underlying data, reporting, and alerting practices.
- Establish repeatable processes for customer retrospectives and proofs of concept.
- Identify recurring fraud signals and product opportunities.
- Review analytical designs, data models, code, and model evaluations.
- Contribute directly to critical customer investigations.
- Coach data scientists through feedback, performance discussions, and growth opportunities.
- Define, evaluate, and improve Fraud product performance.
- Translate customer insights and fraud analyses into scalable product capabilities.
- Lead and develop a high-performing team.
Benefits
- Equity and/or commission
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)