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.
As part of our growing Data Science and Analytics team, you will lead the Supply DS pillar and play an instrumental role in our company's mission of building safe and beneficial AI. Anthropic is completely supply-constrained — how we allocate compute is one of the highest-leverage decisions we make, and today that allocation is tied only minimally to user outcomes like retention and LTV. You'll change that.
Embedded with our infrastructure leadership, you'll build the quantitative foundation — observational analyses, synthetic experiments, and optimization frameworks — for how Anthropic allocates its most scarce resource. In this unique company, technology, and moment in history, your work will directly shape how frontier AI reaches the world at scale.
Responsibilities:- Build and grow the Supply Data Science team, raising the bar for talent and shaping the culture of the pillar
- Design a testing framework — observational and synthetic — to quantify how different inputs affect compute allocation outcomes
- Tie compute allocation decisions to downstream user outcomes (retention, LTV, revenue) so we stop optimizing in a vacuum
- Measure and improve how AI affects our own developer productivity inside Anthropic
- Represent the DS organization in senior leadership forums with our CTO and his staff, owning the narrative on compute and supply
- Uplevel reporting, metrics, and shared understanding of the supply area across the company
- Establish foundational data practices and scale analytics infrastructure to support rapid iteration as we grow
- 10+ years of technical IC / tech-lead-manager experience in data science, analytics, or operations research
- A strong Operations Research background — you think natively in terms of optimization, constrained allocation, and queueing
- Direct experience embedded with high-performing engineering teams, not at arm's length from the system
- Experience working on highly complex systems with many interacting components (ad networks, credit-card processing, marketplace matching, routing, etc.)
- A track record of owning and presenting analyses in high-pressure executive forums — you can take a punch and still move the room
- Deep expertise with Python, SQL, and data visualization tools
- A passion for the company's mission of building helpful, honest, and harmless AI
- Experience with causal inference methods applied to operational decisions (synthetic controls, geo-experiments, switchbacks)
- Experience designing experimentation platforms from scratch, not just using them
- Exposure to AI/ML products, large language models, or large-scale inference systems
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.
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 their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Anthropic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.
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Strong & Reliable Incentives — Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
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Healthcare Strength — Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
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Parental & Family Support — Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.
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What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
