Be the first to hear about new sota jobs + exclusive salary research + career cheatsheets.
Anthropic · San Francisco/New York City/Seattle · Hybrid
Data Scientist, Marketing
3/24/2026
Description
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
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
Nice to have
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