Senior Data Scientist
Senior Data Scientist on Plaid's Network Value team supporting the Guard product. Translate product questions into analysis, build metrics/OKRs/dashboards, run experiments, and drive data-informed decisions for a 0-to-1 user-facing fintech product.
About the job
Responsibilities
- Champion a data-first approach to decision-making across the organization as Guard is built and scaled, serving as the data and analytical thought partner to product managers, engineers, and cross-functional stakeholders.
- Translate ambiguous business and product questions into clear analytics projects and decision frameworks, and perform ad-hoc and strategic analyses to identify opportunities to improve user outcomes and business performance.
- Build and maintain data models, dashboards, core metrics, OKRs, and success metrics that improve visibility into Guard performance and quantify progress against business goals.
- Design and analyze experiments to support feature launch and iteration decisions, and partner on Airflow- and dbt-powered data pipelines that enable trustworthy analytics and scalable reporting.
- Identify novel ways to impact top-line OKRs and influence stakeholders on prioritization, roadmapping, and execution, while exploring ML prototypes and causal inference approaches where they can improve product or decision quality.
Qualifications
- 5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role
- Fintech experience, including experience working with raw fintech data
- Experience launching direct-to-consumer products from 0 to 1
- Experience with experimentation, ad-hoc analysis, and developing strategic insights
- Strong SQL skills and experience creating metrics that drive alignment with stakeholders
- Experience building or partnering closely on data pipelines using Airflow and dbt
- Strong communication skills and experience partnering cross-functionally with product managers, engineers, and other stakeholders
- Experience driving data-driven performance for user-facing products
- Track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or execution
Nice-to-Haves
- Experience with causal inference
- Experience with machine learning
- Python proficiency
Skills
SQL, Airflow, dbt, Python, Machine Learning, Causal Inference, Experimentation, Data Modeling, Dashboarding, Okrs, Metrics Development
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