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Senior Data Scientist, Causal Inference

Develops models and data products using causal inference to measure marketplace impacts like pricing tools and recommendations. Requires 5+ years experience (BS/MS) or 2+ (PhD), strong Python/SQL/R coding, ML, and experimentation skills.

179k – 210kUnited StatesData ScienceRemote5+ YOE

About the role

Responsibilities

  • Build strong relationships with cross-functional partners across Product, Design, Engineering, and Analytics to drive collaboration and innovation.
  • Contribute directly to the development and launch of data-driven products and models, leveraging AI tools to enhance efficiency and impact.
  • Write software in Python, SQL, or R to model, simulate, and measure the impact of new features, applying advanced causal inference techniques.
  • Analyze structured or unstructured data to uncover meaningful insights and craft actionable proposals that help shape strategy.
  • Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed data-driven decision making.

Requirements

  • 5+ years of experience with BS/masters degree, 2+ years of experience with PhD.
  • Experience with experimentation, causal observational analysis, and machine learning techniques.
  • Experience partnering with product, engineering, and design to enable data-driven model or product development.
  • Ability to prototype, build, and scale derived data assets.
  • Strong coding skills in SQL and either Python or R.
  • Strong oral and written communication skills - an ability to communicate complex technical concepts to a non-technical audience.

Nice-to-Haves

  • Work authorization (if applicable)
  • Travel requirements (if applicable)

Compensation

Pay Range: $179,000—$210,000 USD (base pay). Role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Skills

PythonSQLRCausal InferenceMachine LearningExperimentationCausal Observational Analysis

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