Data Science, Finance & Strategy
Anthropic · San Francisco, CA · Finance · listed April 10, 2026
The shape of it
Seniority
Not stated
Where
Hybrid
Stated pay
$270,000 – $320,000 USD
Requirements listed
6
Length
1,111 words
In the posting’s own words
You’ll 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 you’ll operate as an analytical lead, partnering closely with Product Finance and our model performance Data Science teams.
What it asks for · 6
- 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
- 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: 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
Also a plus
- 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
What the job covers
- 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
Tools and skills named
Cloud & infra
- AWS
- CI/CD
- GCP
- Observability
Languages
- Python2×
- SQL2×
Models & research
- Evaluations
- LLM
Data
- dbt
Frameworks
- REST
Go to market
- Forecasting
Ways of working
- Testing
Words the posting leans on
- model10×
- market9×
- product8×
- data6×
- analytics5×
- pricing5×
- finance4×
- packaging4×
- value4×
- around3×
- decisions3×
- experience3×
- launch3×
- questions3×
- senior3×
- analyses2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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