Data Scientist
Senior Data Scientist supporting Plaid’s Credit product area, translating ambiguous product questions into analytics, metrics, experiments, and strategic insights. The role partners closely with product and engineering teams and requires 5+ years of data science or related analytics experience.
About the job
Responsibilities
- Champion data-first decision-making and help teams use evidence to set direction.
- Partner with product managers, engineers, and cross-functional stakeholders to define problems, shape product strategy, and execute roadmaps.
- Translate ambiguous business and product questions into analytics projects, decision frameworks, and measurable outcomes.
- Perform ad hoc and strategic analyses to identify opportunities to improve product performance, user experiences, and business results.
- Build and maintain data models, dashboards, metrics, OKRs, and KPIs for Credit systems.
- Design and analyze experiments supporting feature launches, iteration, and ship decisions.
- Partner on dbt- and Airflow-powered data pipelines and create reliable, scalable analytics.
- Identify opportunities to influence top-line OKRs and advise prioritization, roadmapping, and execution decisions.
- Help shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network.
Requirements
- 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 stakeholder alignment and decision-making.
- Experience driving data-informed performance improvements for user-facing products.
- Experience building or closely partnering on data pipelines using tools such as Airflow and dbt.
- Track record of influencing top-line OKRs and stakeholder prioritization, roadmapping, or execution.
- Strong communication skills, including explaining analytical methods, tradeoffs, and recommendations to technical and cross-functional partners.
Nice-to-haves
- Fintech experience, including work with raw fintech or financial transaction data.
- Experience with causal inference or machine learning.
- Python proficiency.
Compensation and Benefits
- Annual salary range: $190,800–$262,800.
- Additional compensation may include equity and/or commission, depending on the position offered.
- Comprehensive benefits include medical, dental, vision, and 401(k).
Skills
SQL, Python, Redshift, Databricks, dbt, Apache Airflow, Data Modeling, Experimentation, Causal Inference, Machine Learning, Dashboarding
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