Data Science, Finance & Strategy

About the role

Anthropic’s 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?

Key Responsibilities

• 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 it's 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 team’s product-finance analytics practice by example

Minimum Qualifications

• Put shape around ambiguity: you’ve 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 you’d rather ship a defensible v1 with honest error bars than wait for perfect data
• 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: you’re 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

Preferred Qualifications

• 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

Annual Compensation Range

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 $270,000—$320,000 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.

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.

Guidance on Candidates' AI Usage

Learn about our policy for using AI in our application process.