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PlaidPlaidSan Francisco, CA

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.

191k – 263k
Hybrid5+ YOEData Science

About the role

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

SQLAirflowdbtPythonMachine LearningCausal InferenceExperimentationData ModelingDashboardingOkrsMetrics Development

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