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
A/B Testing @ 3
Data Science @ 3
Communication @ 3
API @ 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
As part of the Data Science and Analytics team, you will drive data-informed decision-making across the organization while embedded with teams supporting the Developer Platform — the infrastructure that enables developers and enterprise customers to build on Claude via the core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You will partner closely with product, engineering, and go-to-market teams to understand how AI agents are being built and deployed at scale, identify growth opportunities, surface insights about platform adoption, and drive data-informed decisions that shape the platform roadmap. You will also help establish analytical foundations and best practices for a growing data science function.
Responsibilities
- Define key metrics, build measurement frameworks, and maintain core reporting to evaluate platform success
- Conduct deep dives into product and usage data to surface actionable insights, size opportunities, and influence roadmaps across product, engineering, and go-to-market teams
- Develop hypotheses and apply rigorous causal inference methods (including controlled experiments and synthetic controls) to evaluate platform changes and make actionable recommendations
- Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
- Build statistical models, optimization frameworks, and simulations to support and automate operational and decision-making processes
- Present complex analyses and recommendations clearly to both technical and non-technical stakeholders
- Help establish foundational data practices and scale analytics infrastructure to support rapid iteration as the platform grows
Requirements (Minimum qualifications)
- Proficiency in Python, SQL, and data visualization tools
- Expertise in experimental design, causal inference, statistical modeling, and A/B testing, particularly in high-scale technical environments
- Experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy
- Effective written communication and presentation skills, with the ability to translate complex analyses into clear, actionable recommendations for both technical and business audiences
Preferred qualifications
- 6+ years of experience in data science or analytics roles
- Experience supporting B2B sales teams with data insights
- Strong instincts for what drives product adoption, engagement, and retention in developer or enterprise contexts
- Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem
- Comfort operating in ambiguous, fast-moving environments where creating clarity is part of the role
- A genuine interest in Anthropic's mission of building safe and beneficial AI
Compensation
- Annual Salary: $275,000 - $370,000 USD
Logistics
- Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
- Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time (some roles may require more time in office)
- Visa sponsorship: Anthropic states they do sponsor visas and will make reasonable efforts to obtain a visa for hired candidates and retain an immigration lawyer to assist
Benefits
Anthropic states they offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office space for collaboration.
How we're different
Anthropic emphasizes large-scale, collaborative research on high-impact AI safety and reliability topics and values strong communication and cross-disciplinary collaboration. Candidates are encouraged to review recent research and the company's mission.