Data Scientist, North Insights

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 Data Scientist on our Analytics and Data Insights team, you'll work on problems that don't have textbook answers yet; building the analytics that shape product and company strategy, designing the experiments that prove or kill our biggest bets, and helping enterprise customers understand what foundational AI actually means for their bottom line.

You'll own analytical work end-to-end: from framing the right questions and building the models to shipping insights, tools, and results that product leaders, sales teams, and enterprise customers rely on.

- Build bleeding-edge agentic analytics: Agentic analytics is far from a solved problem, and we want to be the company that solves it. We need the sharpest minds with the curiosity, drive, and focus required to build the tools necessary to bring order and clarity to real world data.

- Define AI impact measurement: own the end-to-end analytics story around adoption, growth, and impact that North leadership uses to prioritize features by measured value rather than customer feedback alone.

- Ship customer-facing analytics: insights that our enterprise customers recognize as evidence of value created.

- Build small language models to categorize, classify, and enrich message data to give customers visibility into how their teams are using our products in their enterprise.

- Design and run experiments: A/B tests, causal inference studies, and opportunity sizing 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.

- Act like an owner: no waiting around. You'll define analytical priorities within your scope, push initiatives from question to production, and own what you build.

- Strong command of SQL, Python, and Git, alongside 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 building and deploying production models, not just notebook analysis. You know what it takes to get a classifier down the stack from prototype to production volume.

- 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 weedsComfort operating in ambiguity, managing multiple workstreams across different stakeholders, and distilling insights into a concise, actionable narrative

- A collaborative style grounded in empathy as much as in data; you work alongside product, research, sales, and finance, not in a silo

If some of the above doesn't line up perfectly with your experience, we still encourage you to apply!