Data Scientist, Marketing

Data Scientist, MarketingNew York City, NY | Seattle, WA; San Francisco, CAAbout AnthropicAnthropic'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 RoleAs 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 ResponsibilitiesOwn 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 itTranslate measurement results into budget and channel recommendations that shape how marketing investsEstablish primary success metrics and guardrails for lifecycle marketing, anchored on activation and active usage rather than reachDevelop hypotheses on marketing interventions, design experiments or causal inference studies, analyze results, and make recommendations based on impact to key metricsMake 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 loopPresent complex technical analyses and recommendations to both technical and non-technical audiencesMinimum QualificationsHands-on experience with marketing incrementality methods, including marketing mix modeling, geo experiments, synthetic controls, and A/B or holdout testing at scaleProficiency with causal inference and machine learning methods, and judgment about when each is appropriateProficiency with Python and SQLExperience applying data science within a Marketing or Growth contextAbility to communicate complex analyses as clear recommendations for non-technical audiencesPreferred Qualifications7+ years of experience in data science, with significant time embedded in Marketing or Growth teamsExperience building measurement frameworks from the ground up, moving teams from descriptive reporting toward causal understandingA track record of translating complex analyses into recommendations that senior marketing stakeholders act onExperience bringing marketing mix modeling in-house, or operating one end-to-end rather than through a vendorExperience defining activation metrics and lifecycle measurement for a product-led businessBackground at consumption-based, multi-product companies serving both consumers and enterprisesComfort setting direction and making decisions when requirements are still taking shapeAn interest in Anthropic's mission of building safe and beneficial AIThe 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 USDLogisticsMinimum education: Bachelor's degree or an equivalent combination of education, training, and/or experienceRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experienceMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the positionLocation-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. 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 DifferentWe 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.The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.Come Work With Us!Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.