Analytics, Finance & Strategy

About the role As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by delivering the analysis and analytics infrastructure that shape how Finance & Strategy (F&S) understands Anthropic's business. In this unique company, technology, and moment in history, your work will directly inform how leadership navigates one of the fastest-growing businesses in the world. This is a role spanning data analysis, business intelligence and analytics engineering, partnering closely across several cross functional teams including Data Engineering, Data Science & Analytics, and Finance & Strategy. You will produce high-impact, high-visibility analyses that answer leadership's most pressing questions about the financial trajectory of the business—revenue drivers, margin dynamics, compute economics, customer segments, and the forces shaping our P&L. You'll also build the datasets, pipelines, and BI foundations that make those insights possible at scale and ensure every number the executive team sees is one they can trust. You've worked in cultures of excellence in the past and are eager to apply that experience to both the craft of analysis and the rigor of building durable data systems as our company goes through a phase of rapid growth. Key responsibilities Deliver high-impact analyses and deep dives that surface key insights about Anthropic's financial performance directly to finance and executive leadership. Build and maintain canonical datasets, dashboards, and scaled reporting solutions that provide real-time financial visibility across the company. Partner with Finance & Strategy teams (Product, Compute, GTM, and Corporate) to answer their most important questions and streamline recurring analytical workflows. Establish analytics engineering and BI best practices for F&S, including data management, governance, and reporting standards. Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines supporting finance and accounting analytics. Champion data-informed decision making across the organization. Experience spanning data analysis, business intelligence, and/or analytics engineering, ideally with exposure to Finance & Strategy, Data Infrastructure and Analytics Engineering. Highly proficient in SQL and Python for analysis, data manipulation, ETL/ELT, and automation. Track record of producing analyses that have meaningfully influenced business or leadership decisions. Extensive experience with data visualization and using AI tools for data analysis and BI. Experience with cloud platforms (AWS, GCP) and modern data stack tools (dbt, Airflow, etc.). Hands-on experience working with financial systems and building downstream data models from these systems. Able to translate complex business questions into both sharp analyses and durable technical solutions, and can communicate effectively with technical and non-technical stakeholders, including executives. Detail-oriented with a deep commitment to data accuracy. Thrives in fast-paced environments, can manage multiple priorities while maintaining high-quality deliverables. Operates with an ownership mindset, taking projects end-to-end from ambiguous question to trusted answer and seeing them through to impact. Preferred qualifications 6+ years of hands‑on experience spanning data analysis, business intelligence, and/or analytics engineering. Championed AI driven analytics and financial analysis within their organizations. Prior experience in high‑growth technology companies or startups. Strong financial acumen with deep understanding of finance principles. Knowledge of statistical analysis and advanced analytics techniques. Familiarity with data governance best practices and experience implementing data quality frameworks. Compensation

$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. If we make you an offer, we will make every reasonable effort to get you a visa. Equal Employment Opportunity As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. #J-18808-Ljbffr anthropic