Used Tools & Technologies
Machine Learning LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 5
SQL @ 5
Data Science @ 3
Leadership @ 3
Communication @ 3
Mentoring @ 3
Experimentation @ 3
Reporting @ 3
AI @ 3
Data Visualization @ 5
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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
Requirements
- Strong technical IC background in data science, analytics, or operations research
- Operations research foundation — 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
Compensation
Annual Salary: $275,000 - $370,000 USD
Locations & Office Policy
San Francisco, CA; New York City, NY
Location-based hybrid policy: currently we expect all staff to be in one of our offices at least 25% of the time.
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
- Deadline to apply: None. Applications are accepted on a rolling basis.
Visa Sponsorship
We do sponsor visas. 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.
How we're different
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. We value impact, communication skills, and collaborative research discussions. The posting references prior research directions (GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences).
Apply
Candidates are encouraged to apply even if they do not meet every qualification listed. Anthropic provides guidance on candidate AI usage during the application process.