Senior Data Scientist - Network Value

Plaid Plaid · Fintech · San Francisco, CA · All Cost Centers

Senior Data Scientist at Plaid focused on network value and consumer fintech products. Responsibilities include building ML prototypes, causal inference models, performing ad-hoc and strategic analysis, designing and analyzing experiments, and creating data models and dashboards to support product development and OKRs.

What you'd actually do

  1. Champion a data-first approach toward decision-making across the entire organization
  2. Become the data and analytical thought partner to product managers and engineers
  3. Translate business questions into analytics projects
  4. Perform ad-hoc and strategic analyses to identify opportunities for improved outcomes and support business decisions
  5. Build data models and dashboards to improve visibility into core systems
  6. Create OKRs quantifying progress against business goals
  7. Design and analyze experiments to support feature ship decisions
  8. Build ML prototypes and causal inference models

Skills

Required

  • 5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role
  • Experience with experimentation, ad-hoc analysis, and developing strategic insights
  • Strong SQL skills and experience creating metrics that drive alignment with stakeholders
  • Experience building data pipelines with 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 have

  • Fintech experience and experience working with raw fintech data
  • Experience with causal inference, machine learning, and Python

What the JD emphasized

  • ML prototypes
  • causal inference models

Other signals

  • ML prototypes
  • causal inference models
  • experimentation
  • data modeling
  • dashboarding