Lead Data Scientist, Platform Product

In this role, you'll partner closely with product, engineering, and go-to-market teams to understand how AI agents are being built and deployed at scale. You'll identify growth opportunities, surface insights about platform adoption, and drive data-informed decisions that shape our platform roadmap. You'll also help establish the analytical foundations and best practices of a data science team that is still defining itself — bringing rigor and clarity to a fast-moving environment.

Key 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

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

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:

$285,000—$380,000 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 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.

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. 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.