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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 own the measurement strategy behind Anthropic's marketing investment. This is a foundational role, building marketing measurement at Anthropic from the ground up. Your first focus is paid media. We are bringing marketing mix modeling in-house, and you will build and operate the econometrics toolkit — marketing mix modeling (MMM), geo experiments, synthetic controls, and incrementality testing — that tells us which marketing investments actually drive growth, working in close partnership with our paid marketing data scientist. From there, you'll extend the same causal rigor to lifecycle and other marketing programs: defining success metrics oriented on activation and sustained usage, and building self-serve measurement that scales beyond any one embedded analyst. Key responsibilities Own incrementality measurement for paid media: build and operate our in-house marketing mix model, and design the geo experiments, synthetic-control studies, and holdouts that validate and calibrate it Translate measurement results into budget and channel recommendations that shape how marketing invests Establish primary success metrics and guardrails for lifecycle marketing, anchored on activation and active usage rather than reach Develop hypotheses on marketing interventions, design experiments or causal inference studies, analyze results, and make recommendations based on impact to key metrics Make marketing measurement self-serve by establishing the metrics, tooling, and best practices that let marketing partners answer routine questions without a data scientist in the loop Present complex technical analyses and recommendations to both technical and non-technical audiences Minimum qualifications Hands-on experience with marketing incrementality methods, including marketing mix modeling, geo experiments, synthetic controls, and A/B or holdout testing at scale Proficiency with causal inference and machine learning methods, and judgment about when each is appropriate Proficiency with Python and SQL Experience applying data science within a Marketing or Growth context Ability to communicate complex analyses as clear recommendations for non-technical audiences Preferred qualifications 7+ years of experience in data science, with significant time embedded in Marketing or Growth teams Experience building measurement frameworks from the ground up, moving teams from descriptive reporting toward causal understanding A track record of translating complex analyses into recommendations that senior marketing stakeholders act on Experience bringing marketing mix modeling in-house, or operating one end-to-end rather than through a vendor Experience defining activation metrics and lifecycle measurement for a product-led business Background at consumption-based, multi-product companies serving both consumers and enterprises Comfort setting direction and making decisions when requirements are still taking shape An interest in Anthropic's mission of building safe and 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: $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