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Lead Data Scientist

San Francisco, CANew York, NYData ScienceRemote
Summary

Lead data scientists design and execute experiments like A/B tests and causal inference to inform product and go-to-market decisions, build predictive models for forecasting and segmentation, and manage a team of analysts while shaping company strategy.

About the role

Responsibilities

  • Own the science: design and lead experimentation programs including A/B tests, multi-armed bandits, causal inference studies, that directly map to product and go-to-market decisions.
  • Build predictive models that matter: develop and deploy models for forecasting, segmentation, propensity scoring, and opportunity sizing across Cohere's core business lines.
  • Lead and grow a team: manage a team of analysts and data scientists. Set the technical bar, mentor aggressively, and create an environment where exceptional people do their best work.
  • Act like an owner: define analytical priorities, allocate resources, and push initiatives from question to production.
  • Shape strategy: partner across product, research, sales, and finance to define how Cohere grows. Your team's work will get built into products and implemented into strategy.

Requirements

  • Strong command of SQL, Python, and Git, alongside deep expertise in statistical inference, experimental design, and predictive modeling.
  • Proven ability to turn ambiguous business questions into rigorous analytical problems, with clear and compelling recommendations.
  • Experience leading analytics or data science teams, with a track record of making smart people faster.
  • Familiarity with modern data stack tools such as BigQuery, dbt, Looker, or Airflow (nice to have).
  • Comfort operating in ambiguity, managing complex multi-workstream roadmaps, and distilling insights into a concise, actionable narrative.
  • Genuine excitement about AI.

Nice-to-Haves

  • Leadership style grounded in empathy as much as in data.
Skills
SQLPythonGitBigQuerydbtLookerAirflowA/B TestingCausal InferencePredictive Modeling