Data Scientist

About the role

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.

What excites you

• 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.

Must-have Qualifications

• 5–8+ years of experience as a Data Scientist or in a related analytics or data-focused role.
• Experience as a product data scientist helping grow an early-stage or consumer-facing product, ideally from 0 to 1.
• Experience with experimentation, ad-hoc analysis, and strategic insight generation in a product environment.
• Strong SQL skills and experience creating metrics that drive alignment and decision-making with stakeholders.
• Experience driving data-informed performance improvements for user-facing products.
• Experience building or partnering closely on data pipelines using tools such as Airflow and dbt.
• A track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or execution.
• Strong communication skills and the ability to explain analytical methods, tradeoffs, and recommendations to product managers, engineers, and other cross-functional partners.

Nice-to-have Qualifications

• Fintech experience, including experience working with raw fintech or financial transaction data.
• Experience with causal inference or machine learning.
• Python proficiency.