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Accounting Analytics & BI Engineer

Anthropic · San Francisco, CA

Location
San Francisco, CA
Posted
Yesterday
Engineering

About this role

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

As a member of our Finance Analytics and Business Intelligence team, you'll play an instrumental role in our company's mission of building safe and beneficial AI by establishing the analytics engineering and business intelligence capabilities our Accounting organization runs on. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining accounting processes, and supporting financial operations as we deploy safe, frontier AI at scale to the world.

You'll partner closely with the Accounting organization to build the data foundation that turns financial and operational data into reliable, self-serve insight and automated processes. That means owning the data models and orchestration beneath accounting analytics, designing the dashboards and data applications stakeholders rely on day to day, and partnering across Data Engineering, Data Science, and the broader Finance organization to make sure every number is one the team can trust. Increasingly, it also means defining the future of AI-powered accounting automation; finding where AI can take on work that is manual today and reshape how the function operates.

This is a foundational, hands-on role at the intersection of accounting, analytics, and business intelligence. You'll establish the durable, scalable systems the fast-growing function depends on, bringing the rigor of a culture of excellence to a function still being built from the ground up, and taking projects end to end, from an ambiguous question to a trusted, scalable system.

Key responsibilities

  • Design, build, and maintain data models and orchestration pipelines (dbt, Airflow) that power analytics, reporting, and downstream financial workflows
  • Develop dashboards, visualizations, and data applications that give stakeholders self-serve access to their data
  • Translate stakeholders' business questions into well-defined metrics and tools, and turn the resulting analysis into clear recommendations
  • Build analytics that support financial reporting, the close process, reconciliations, and scenario analysis
  • Define the future of AI-powered accounting automation in partnership with stakeholders, streamlining workflows and reducing manual effort
  • Champion data quality, testing, and documentation across the data stack

Minimum qualifications

  • Proficiency in SQL and Python (or another object-oriented programming language)
  • Experience with data modeling and orchestration tools (e.g., dbt and Airflow)
  • Experience with data visualization and business intelligence tools (e.g., Looker, Tableau, Hex, Streamlit)
  • Experience designing self-serve analytics experiences for non-technical stakeholders
  • A track record of partnering closely with Finance or Accounting teams to drive business and financial outcomes, turning open questions and data into clear, insightful analysis

Preferred qualifications

  • Experience using AI to improve or automate analytical processes
  • Experience building data applications
  • Experience with cloud computing platforms (e.g., AWS, GCP) and their cost structures
  • Experience modeling financial impact, including forecasting and scenario analysis
  • A bias for action and urgency, not letting perfect be the enemy of effective
  • A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress
  • A deep curiosity and energy for pulling the thread on hard questions
  • A passion for Anthropic's mission of building safe, beneficial AI

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:$220,000-$270,000 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. 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.

As published by Anthropic. Applications are handled on their site.

About Anthropic

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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