Data Science, Finance & Strategy

Anthropics 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.

Anthropics Finance Analytics & Business Intelligence team is hiring a senior individual contributor to own how we measure the value of our models and our position in the market. These are open questions without an established playbook: how much value do our models deliver per dollar and per token how is that changing with every launch how do we compare to the rest of the frontier

Youll own how Finance quantifies relative model value and market position: maturing our cross-product benchmark suite building task-cost and price-elasticity estimates that inform live pricing and packaging decisions sourcing and running capability and market analysis around every model launch and standing up forecasting on third-party and survey data. The work is open-ended and technical and youll operate as an analytical lead partnering closely with Product Finance and our model performance Data Science teams.

• Build the relative-value measurement system: evolve our cross-product benchmark into a durable trusted read on model and product value spanning coding agentic and product-shaped tasks
• Inform pricing and packaging: construct task-cost approximations and price-elasticity estimates across differently priced products and carry them into decisions
• Own launch and market analytics: run analytics around model launches including capability-based revenue analyses and views of the broader market
• Deepen our market understanding: evaluate and integrate external datasets and research to strengthen our read on the market and how its evolving
• Partner with Product Finance: take open-ended pricing packaging and positioning questions from vague ask to decision-grade answer
• Raise the bar: land narratives in executive forums and uplevel the teams product-finance analytics practice by example

• Put shape around ambiguity: youve personally defined the measurement approach for questions nobody knew how to answer without waiting for a fully specified ask
• Land narratives with executives: your analyses have changed pricing product or competitive decisions and you can simplify for senior leaders without losing rigor
• Stay hands-on at senior scope: you still write the SQL and Python yourself and youd rather ship a defensible v1 with honest error bars than wait for perfect data
• Are inherently curious: you go one level deeper than asked and are energized by how fast models products and the market are moving
• Thrive amid shifting priorities: you juggle multiple fast-moving workstreams and stay effective when the plan changes weekly
• Work fluently with modern tooling: youre strong at data visualization use Claude and AI tools as force multipliers in analysis and BI and can self-serve your own workflows across SQL Python dbt and a cloud warehouse

• Experience designing evals or benchmarks for AI models or products
• Pricing and packaging analytics at scale including elasticity estimation
• Market share estimation from imperfect third-party panel or survey data
• Fluency in the LLM model and product landscape
• Dimensional modeling and warehouse design experience (grain SCDs point-in-time correctness)
• Cloud platform experience (AWS GCP) with orchestration CI/CD for data and testing/observability

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit 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. Were 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.

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 aboutour policy for using AI in our application process.