Data Scientist, Developer Productivity
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.
What this role actually needs.
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. Responsibilities: - Define key metrics, build measurement frameworks, and maintain core reporting to evaluate developer productivity and engineering effectiveness - Deep dive into product and user data to derive actionable insights, size opportunities, and influence roadmaps through clear recommendations - Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to 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 automate decision-making and operational processes - Present complex analyses and recommendations to both technical and non-technical stakeholders Requirements: - Working expertise with Python and SQL - Working expertise with data visualization tools - Hands-on experience with experimental design, causal inference, statistical modeling, and A/B testing frameworks - Strong written communication and presentation skills - Track record of translating complex data into clear, actionable insights for both technical and business stakeholders Company context: Anthropic is an AI safety company building Claude, a frontier-model assistant for developers, enterprises, and consumers.
Day-to-day expectations
Anthropic lists these responsibilities for the Data Scientist, Developer Productivity role.
- Define key metrics, build measurement frameworks, and maintain core reporting to evaluate developer productivity and engineering effectiveness
- Deep dive into product and user data to derive actionable insights, size opportunities, and influence roadmaps through clear recommendations
- Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to 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 automate decision-making and operational processes
- Present complex analyses and recommendations to both technical and non-technical stakeholders
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- Working expertise with Python and SQL
- Working expertise with data visualization tools
- Hands-on experience with experimental design, causal inference, statistical modeling, and A/B testing frameworks
- Strong written communication and presentation skills
- Track record of translating complex data into clear, actionable insights for both technical and business stakeholders
Why this listing is more than a copied job post.
Data Scientist, Developer Productivity is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
United States roles on UpJobz are filtered for high-tech relevance, source freshness, and actionable employer detail before they are allowed into SEO surfaces.
Compensation read
The employer source does not expose a reliable salary range, so candidates should ask for compensation early instead of waiting until late-stage interviews.
Work authorization read
Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
On-site roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.
Browse similar jobs
Turn this listing into an application plan.
This is the first pass at the premium UpJobz layer: a fast brief that helps serious applicants move with more clarity.
Next moves
- Tailor your resume around ai and llm instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to data scientist, developer productivity is a high-signal on-site role in san francisco, and it is most realistic for open to tn, h-1b, and opt candidates already in the united states.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
Keywords to match against your background
Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.
Apply through the employer source
Open the source listing from job-boards.greenhouse.io, confirm the role is still active, then apply on the employer or ATS page.
Source: job-boards.greenhouse.io · Source ID: 5197529008 · Confidence: 97/100 · Last checked: May 7, 2026
How UpJobz verifies job sourcesContinue browsing tech jobs