Data Scientist, North Insights

Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Why this role?

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.

As a Data Scientist, you will:

• Drive the mission forward.
• 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.