Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 5
SQL @ 5
GCP @ 3
dbt @ 3
ETL @ 5
Airflow @ 3
Data Science @ 3
Leadership @ 3
AWS @ 3
Communication @ 6
Data Engineering @ 3
Data Analysis @ 3
ELT @ 5
BI @ 3
Reporting @ 3
AI @ 3
Data Visualization @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Finance Analytics and Business Intelligence team delivers the analysis and analytics infrastructure that shape how Finance & Strategy (F&S) understands Anthropic's business. This role spans data analysis, business intelligence, and analytics engineering, partnering closely with Data Engineering, Data Science & Analytics, and Finance & Strategy to produce high-impact analyses and build durable data systems.
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
Requirements
- 6+ years of hands-on 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 Claude / 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
- Ability to translate complex business questions into both sharp analyses and durable technical solutions; strong communication with technical and non-technical stakeholders, including executives
- Detail-oriented with a deep commitment to data accuracy; able to manage multiple priorities in fast-paced environments and own projects end-to-end
Preferred qualifications
- Experience championing AI-driven analytics and financial analysis within 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
Annual Salary: $270,000 - $320,000 USD
Logistics
- Location: San Francisco, CA (Anthropic headquarters)
- Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
- Location-based hybrid policy: staff expected to be in an office at least 25% of the time (some roles may require more)
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist, though not every role or candidate can be guaranteed sponsorship
How we're different
Anthropic values collaborative, high-impact AI research and communication skills. The team works on a few large-scale research efforts and emphasizes impact, empirical science, and frequent research discussions.