Data Scientist, Capacity Operations at ANTHROPIC PBC DBA ANTHROPIC INC

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

01 May, 26

Salary

370000.0

Posted On

31 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Data Analysis, Python, SQL, Predictive Models, Resource Allocation, AI/ML Products, Large Datasets, Real-Time Streaming Data, Communication Skills, Cloud Based Billing Systems, API Rate Limiting, Inference Workload Patterns, Accelerator Management, Finance Collaboration, GTM Teams

Industry

Research Services

Description

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 an early member of our Data Science and Analytics team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by ensuring we strategically manage and scale our computing resources to meet research and product needs. In this unique company, technology, and moment in history, your work will be critical to ensuring our infrastructure is efficient, scalable, and ready to support the deployment of safe, frontier AI at scale to the world. You will work closely with infrastructure engineers, product, and finance to understand current utilization patterns, identify optimization opportunities, and build models to forecast future capacity requirements. You've worked in cultures of excellence in the past and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth. Responsibilities: Analyze infrastructure and utilization data to define key metrics, understand trends, and identify and size opportunities to optimize costs and performance — influencing the roadmap through your insights and recommendations. Develop models to forecast future capacity needs based on business growth projections and product roadmaps. Partner with stakeholders across engineering, research, product, operations and finance to improve predictability of capacity utilization and optimize the allocation of capacity across different users and products. Build a data-driven culture within the compute team by establishing foundational data best practices and making data more accessible. You may be a good fit if you have: 6+ years of experience in data science roles: defining meaningful metrics, building predictive models, developing simulations, and solving resource allocation problems Strong skills in Python, SQL, and data analysis tools, with experience working with large datasets and real-time streaming data A bias for action and urgency, not letting perfect be the enemy of the effective — including in ambiguous environments where you create clarity rather than wait for it. A deep curiosity and energy for pulling the thread on hard questions, turning open-ended inquiry into concise and insightful analysis. Proven ability to translate complex technical analyses into actionable recommendations for diverse audiences, in both written and presented formats. A passion for the company’s mission of building helpful, honest, and harmless AI Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem Strong candidates may have: Knowledge of cloud based billing systems Experience with AI/ML operations & platforms: understanding of API rate limiting, inference workload patterns, accelerator management Experience working closely with Finance teams and/or GTM teams 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: $275,000—$370,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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

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Responsibilities

Analyze infrastructure and utilization data to define key metrics and identify optimization opportunities. Develop models to forecast future capacity needs and partner with stakeholders to improve predictability of capacity utilization.