Data Scientist, Marketing

Anthropic; San Francisco (CA); Hybrid; USD 285,000 - 380,000; Full time

Benefits offered by this job

Hybrid work policy

Visa sponsorship

Competitive compensation

Job summary

Anthropic in San Francisco is seeking a Senior Data Scientist to own the measurement strategy behind our marketing investment. You will build and operate our in-house marketing mix modeling (MMM), geo experiments, synthetic controls, and incrementality testing in close partnership with our paid marketing data science team.

From there, you’ll extend causal rigor to lifecycle marketing, define activation-focused metrics, and develop self-serve measurement that scales beyond any one analyst.

Qualifications

• Hands-on experience with marketing incrementality methods including marketing mix modeling, geo experiments, synthetic controls, and A/B testing at scale.
• Proficiency with causal inference and machine learning methods and knowing when to apply each.
• Experience applying data science within a Marketing or Growth context.
• Ability to communicate complex analyses as clear recommendations for non-technical audiences.

Responsibilities

• Own incrementality measurement for paid media: build and operate an in-house marketing mix model, and design geo experiments, synthetic-control studies, and holdouts to calibrate it.
• Translate measurement results into budget and channel recommendations to shape marketing investments.
• Establish primary success metrics and guardrails for lifecycle marketing centered on activation and active usage.
• Develop hypotheses, design experiments or causal studies, analyze results, and recommend actions based on impact to key metrics.
• Make marketing measurement self-serve by establishing metrics, tooling, and best practices for marketing partners to answer routine questions.
• Present complex analyses and recommendations to both technical and non-technical audiences.

Skills

Marketing incrementality methods

Marketing mix modeling

Geo experiments

Synthetic controls

A/B testing

Causal inference

Machine learning methods

Communication to non-technical

Education

Bachelor's degree

Field relevant to role

Tools

Python

SQL

Job description

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

Compensation

$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. We will make every reasonable effort to obtain a visa if you are offered a role.

Benefits

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.