Data Science, Finance & Strategy
Anthropic · San Francisco, United States · 5mo ago
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. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role
Anthropic's business metrics change quickly. New models, products and pricing land every few weeks, and each one moves the numbers in ways leadership needs to understand and act on quickly.
The Finance Analytics & Business Intelligence team is hiring a senior individual contributor to own how finance leadership reviews key business metrics. You'll run the weekly company metrics update and forum, explain what is driving revenue and usage across products, customers and models, and turn open-ended business questions into clear, data-driven answers. You'll also build what makes those answers repeatable and scalable: governed metric definitions, executive dashboards, and Claude-powered workflows for recurring analysis. The work is technical, fast-moving and highly visible, and it spans Finance, Product, Go-to-Market, Data Science and Data Engineering.
In this role, you will:
- Own the weekly company metrics update and forum: shape the story the numbers tell, evolve the structure and content as fast as the business changes
- Define the metrics that matter: help establish the headline KPIs leadership uses to track the business, and the driver views beneath them.
- Surface macro trends: explain what is driving growth across products, customers, and channels, and flag leading indicators early
- Lead deep dives on executive questions: take a broad question from leadership, put a measurement approach around it, and work with partner teams to deliver a clear, defensible answer
- Track performance against plan: explain where actuals differ from forecast and why it matters
- Partner across teams: work with finance leadership, product and GTM finance and strategy, data science, and data engineering to agree on how we measure the business, so everyone uses the same numbers.
- Raise the bar: land narratives in executive forums and up-level the team’s finance analytics practice by example
You might be a good fit if you:
- Have run an executive metrics forum: you've owned a recurring business review for senior leadership, including its structure, content and discussion.
- Land narratives with executives: your analyses have changed business decisions, and you can simplify for senior leaders without losing rigor
- 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
- 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 work streams 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
Strong candidates may also have:
- Significant experience in finance analytics, business analytics or data science, including direct partnership with senior leadership
- Revenue or growth analytics experience at a usage-based business (cloud, API or marketplace)
- Ownership of a company or executive business review
- Experience designing evals or benchmarks for AI models or products
- Fluency in the LLM model and product landscape
- Experience with a semantic or metrics layer
- 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
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.
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.