Data Scientist, Product

OfferGenie; New York (NY); Hybrid; USD 285,000 - 380,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation & parental leave

Flexible working hours

Office space

Job summary

Anthropic is seeking a senior data scientist to drive data-informed decision making across the organization. You will collaborate with researchers, engineers, and product teams to shape strategy as Anthropic scales.

Responsibilities include designing experiments, building models, defining metrics, and presenting findings to both technical and non-technical stakeholders. You will help scale our analytics infrastructure and data practices in a fast-moving environment.

Qualifications

• 7+ years of experience in data science or analytics roles.
• Deep expertise with Python, SQL, and data visualization tools.
• Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks.
• Strong written communication and presentation skills.
• Track record translating complex data into actionable insights for technical and business stakeholders.
• Bias for action in ambiguous, fast-moving environments.
• Passion for building helpful, honest, and harmless AI and some AI/ML product experience.

Responsibilities

• Deep dive into product and user data to derive actionable insights and size opportunities.
• Develop hypotheses, apply causal inference methods, and analyze results to inform decisions.
• Investigate anomalies and provide data-driven guidance to priorities.
• Define core metrics, build measurement frameworks, and maintain reporting.
• Build statistical models, optimization frameworks, and simulations to automate decisions.
• Present analyses and recommendations to technical and non-technical stakeholders.
• Establish foundational data practices and scale analytics infrastructure as products grow.

Skills

Python

SQL

Data visualization

Experimental design

Causal inference

A/B testing

Communication

Education

Bachelor's degree

Job 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 part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.

Responsibilities:

• Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations
• Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls – and analyze the results in order make actionable recommendations
• Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
• Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success
• Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
• Present complex technical analyses and recommendations to both technical and non-technical stakeholders
• Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow

You may be a good fit if you have:

• 7+ years of experience in data science or analytics roles
• Deep expertise with Python, SQL, and data visualization tools
• Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments
• Highly effective written communication and presentation skills
• A track record of translating complex data into clear, actionable insights for both technical and business stakeholders
• A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress
• 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

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:

$285,000 — $380,000 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 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 [e-mail] 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.