Data Scientist, Marketing

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.

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

Minimum qualifications

• 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
• 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

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.

• 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

$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 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email 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.