Data Scientist

• The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences
• We are a product analytics team embedded in key product areas across Plaid
• We support some of Plaid’s most important OKRs and help execute on product roadmaps
• We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go
• You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio
• You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network
• You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, and support feature-shipping decisions through experimentation
• You’ll also work with SQL, Python, Redshift, Databricks, notebooks, dbt, and Airflow to enable trustworthy analytics and scalable reporting
• Today, Plaid’s Credit business primarily supports income and asset verification solutions
• As cash flow data becomes an increasingly important tool across the lender lifecycle - from acquisition through servicing - you’ll help build cash-flow-based products that enable lenders to approve more borrowers, reduce losses, and reach new segments
• Champion a data-first approach to decision-making across Plaid and help teams use evidence to set direction
• Partner closely with product managers, engineers, and other stakeholders to define problems, shape product strategy, and execute against roadmaps
• Translate ambiguous business and product questions into clear analytics projects, decision frameworks, and measurable outcomes
• Perform ad-hoc and strategic analyses that identify opportunities to improve product performance, user experiences, and business results
• Build and maintain data models, dashboards, core metrics, OKRs, and KPIs that improve visibility into Credit’s systems and quantify progress against goals
• Design and analyze experiments that inform feature launches, iteration, and ship decisions
• Partner on dbt- and Airflow-powered data pipelines and use SQL, Python, Redshift, Databricks, and notebooks to create reliable, scalable analytics
• Identify novel ways to influence top-line OKRs and help stakeholders make thoughtful prioritization, roadmapping, and execution decisions
• Over the next year, shape Credit product strategy, improve product performance and user experience, and contribute to growth of Plaid’s consumer network

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft- Experience driving data-informed performance improvements for user-facing products
• Strong SQL skills and experience creating metrics that drive alignment and decision-making with stakeholders
• Experience with experimentation, ad-hoc analysis, and strategic insight generation in a product environment
• 5–8+ years of experience as a Data Scientist or in a related analytics or data-focused role
• A track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or execution
• Experience building or partnering closely on data pipelines using tools such as Airflow and dbt
• Experience as a product data scientist helping grow an early-stage or consumer-facing product, ideally from 0 to 1
• Strong communication skills and the ability to explain analytical methods, tradeoffs, and recommendations to product managers, engineers, and other cross-functional partners
• We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn’t fully match the job description. We are always looking for team members that will bring something unique to Plaid!
• Fintech experience, including experience working with raw fintech or financial transaction data
• Experience with causal inference or machine learning
• Python proficiency