Lead Data Scientist

We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a Lead Data Scientist on our Analytics and Data Insights team, you'll tackle problems that don't have textbook answers yet; shaping go-to-market strategy for technology that's still being invented, designing the experiments that prove or kill our biggest bets, and helping enterprises understand what foundational AI actually means for their bottom line.

You'll own the full analytical lifecycle, from framing the right questions and building the models, to leading a team that delivers answers leadership can act on.

- 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: no waiting around. You'll 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.

- Strong command of SQL, Python, and Git, alongside deep expertise in statistical inference, experimental design, and predictive modeling

- A proven ability to turn ambiguous business questions into rigorous analytical problems, with clear and compelling recommendations to match

- 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, not essential)

- Genuine excitement about AI - you follow the research, have opinions, and enjoy being in the weeds

- Comfort operating in ambiguity, managing complex multi-workstream roadmaps, and distilling insights into a concise, actionable narrative