Manager, Data Science, GTM

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About The Role

As a Manager on the Data Science team supporting GTM, you will build and lead the team responsible for turning messy, high-stakes commercial data into actionable strategy across all segments and products. You will partner closely with Revenue Operations, Finance, Marketing, Product, and other data teams to connect the needs of our customers to the dynamics of our pipelines — from new logo acquisition through activation, expansion, and retention — for a rapidly scaling consumption-based AI platform.

This team sits at the intersection of fast-moving sales operations and rigorous statistical analysis. In this role, you will balance hands-on technical leadership with people management. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.

Responsibilities

• Build and scale the GTM Data Science team, partnering with RevOps and commercial leaders to solve the hardest and most important data problems to unlock Anthropic’s B2B growth
• Lead a team of data scientists to define metrics, build measurement frameworks, and translate complex analyses into clear recommendations for technical and non-technical stakeholders
• Drive rigorous causal inference and experimentation — controlled experiments, synthetic controls — to surface actionable insights that shape product strategy and roadmaps
• Build and maintain strong partnerships across product, engineering, finance, and leadership — communicating complex analyses clearly and driving alignment on priorities and recommendations
• Own the analytical foundation: statistical models, optimization frameworks, and simulation engines that automate decisions and scale with the business

You May Be a Good Fit If You Have

• 6 years of experience managing data science teams, preferably in a scaling startup environment
• 15 years of total experience in data science or similar data-focused roles
• Deep expertise with Python, SQL, and data visualization tools
• Demonstrated dexterity applying supervised and unsupervised learning techniques across a range of problem types.
• Expertise with causal inference and statistical modeling, particularly in non-experimental or quasi-experimental settings
• A strong track record in multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models
• Expertise with marketing measurement, especially for PLG motions
• Highly effective written communication and presentation skills
• A track record of translating complex data into clear, actionable insights for both technical and business stakeholders
• A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress
• A passion for the company’s mission of building helpful, honest, and harmless AI
• Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary

$450,000—$565,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of th