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About the Role
The Growth team helps more people and companies use and pay for Claude. In this role, you’ll focus on personalization, building and evaluating the models and experiments that choose the right message, offer, or product experience for each user. Your work will span lifecycle marketing, onboarding, and in-product experiences. Claude is a collaborator in much of our analysis, reporting, and experimentation, and you’ll help us find new ways to use it in this work.
Responsibilities
- Build and ship targeting and personalization models that decide which users get which message, offer, or experience, working closely with growth product managers and engineers
- Design tests to evaluate and improve our personalization strategy, including holdouts, bandits, and off-policy estimates where A/B tests aren’t practical
- Design and analyze A/B tests and quasi-experiments across activation, retention, and monetization, and turn the results into actionable recommendations
- Develop a system of metrics and guardrails that connects short-term wins to long-term value
Requirements
- Experience applying data science to growth, lifecycle, or personalization problems
- Experience building and shipping machine learning models that drive user-facing decisions, such as targeting, ranking, recommendation, or personalization
- Experience with experimental design and causal inference, including A/B testing at scale, holdouts, and quasi-experimental methods
- Proficiency in Python and SQL
- Experience communicating analysis in writing and making recommendations that influenced priorities across teams
- Ability to prioritize and make progress when requirements are unclear or changing
- Interest in Anthropic’s mission of building safe and beneficial AI
- 7+ years of experience in data science
- Experience running contextual bandits, uplift models, or similar decision systems in production
- Experience with lifecycle or CRM personalization (email, push, in-product messaging) and its measurement challenges, such as global holdouts and interference between campaigns
- Experience defining activation metrics and lifecycle measurement for a product-led business
- Experience with experimentation platforms and meta-analysis across experiment portfolios
- Experience working on consumption-based, multi-product businesses serving both consumers and enterprises
- Experience using LLMs or coding agents in your analytical workflow
Skills
- Python
- SQL
- Data Science
- Machine Learning
- Experimental Design
- Causal Inference
- A/B Testing
- Contextual Bandits
- Uplift Models
- CRM Personalization
- LLMs
Location
- San Francisco
Work Type
- Hybrid
Experience Level
- 7+ years of experience in data science
Education Level
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
Salary/Compensations
- $285,000—$380,000 USD
Benefits
- Competitive compensation
- Benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
- Lovely office space
About the Company
- 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.
- 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.
- 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.
- Anthropic is a public benefit corporation headquartered in San Francisco.
Equal Opportunity
- 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.