Data Scientist, Supply

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

Anthropic is compute-constrained, and how we allocate that compute is one of the highest-leverage decisions we make as a company. Today, those allocation choices are only loosely tied to the user outcomes we ultimately care about — retention, lifetime value, and the experience of people relying on Claude. You will change that.

As a hands-on technical IC on the Supply pillar of our Data Science & Analytics team, you'll sit alongside the infrastructure engineers who run our compute and help decide how our scarcest resource gets used. You'll design and run the analyses, observational and synthetic experiments, and optimization frameworks that turn opaque supply decisions into shared, measurable understanding across the company. Your work will directly shape how frontier AI reaches the world at scale, and your findings will go in front of senior leadership, including our CTO and his staff.

This role is a fit for someone who thinks natively in terms of constrained allocation and queueing, who enjoys getting close to the system rather than analyzing it from a distance, and who wants their analyses to translate into operational changes that ship.

Responsibilities:

• Build and run testing frameworks — observational and synthetic — to quantify how different inputs affect compute allocation outcomes

• Connect compute allocation decisions to downstream user outcomes (retention, LTV, revenue) so we stop optimizing in a vacuum

• Partner closely with infrastructure engineers, product, and research to instrument the system, measure what matters, and ship operational changes

• Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company

• Contribute analyses and recommendations to executive forums, and co-author the supply narrative the team takes to the CTO and his staff

• Measure and improve how AI affects developer productivity inside Anthropic

You may be a good fit if you have:

• Strong technical IC background in data science, analytics, or operations research

• Operations research foundation — you think natively in terms of optimization, constrained allocation, and queueing

• Deep proficiency with Python, SQL, and data visualization tools

• Track record of owning analyses end-to-end and communicating results clearly to engineering and product leadership

• Direct experience working closely with engineering teams on production systems

• A passion for Anthropic's mission of building helpful, honest, and harmless AI

Strong candidates may have:

• 5+ years of technical IC experience in data science, analytics, or operations research; 8+ years for candidates targeting a Staff-level scope

• Experience with highly complex systems with many interacting components (ad networks, payment processing, marketplace matching, routing, etc.)

• Experience with causal inference methods applied to operational decisions (synthetic controls, geo-experiments, switchbacks)

• Experience contributing to or designing experimentation platforms, not just using them

• Exposure to AI/ML products, large language models, or large-scale inference systems

• Track record of setting technical direction across multiple workstreams or mentoring senior ICs without formal management responsibility

Deadline to apply: None. Applications are accepted on a rolling basis.

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:

$275,000 - $370,000 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 qualific