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
