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Cohere

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Lead experimentation and analytics for Cohere's enterprise AI go-to-market

Cohere is hiring a Lead Data Scientist on its Analytics and Data Insights team to own the full analytical lifecycle for a frontier AI company — designing experimentation programs (A/B tests, multi-armed bandits, causal inference), building predictive models for forecasting and segmentation, and managing a team of analysts and data scientists. This remote-friendly role sits within the Agentic Platform org and works directly with product, research, sales, and finance to shape strategy.

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What this interview tests

  • Experimental design: A/B testing, multi-armed bandits, causal inference
  • Predictive modeling: forecasting, segmentation, propensity scoring, opportunity sizing
  • Team leadership: managing/mentoring analysts and data scientists, setting technical bar
  • Translating ambiguous business questions into rigorous analytical problems
  • SQL/Python/Git fluency and modern data stack familiarity (BigQuery, dbt, Looker, Airflow)
  • Partnering across product, research, sales, and finance to shape strategy

Common question themes

Tell me about an experiment or causal inference study you designed from an ambiguous business question.

How have you built and validated a predictive model (forecasting, segmentation, or propensity scoring) that changed a business decision?

Describe how you've led and mentored a team of analysts or data scientists.

How do you decide between an A/B test, a multi-armed bandit, and a causal inference approach for a given question?

Walk me through turning a vague go-to-market question into a concrete analytical plan.

How do you communicate a technical recommendation to non-technical leadership?

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