Data Scientist, Marketing

Anthropic
San Francisco, CAPosted 24 March 2026

Job Description

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 an early member of our Data Science team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by driving marketing effectiveness through data-driven insights and analytics. In this unique company, technology, and moment in history, your work will be critical to informing our marketing strategy and optimizing our go-to-market approach as we deploy safe, frontier AI at scale to the world. You will work closely with marketing, product, and commercial teams to define and measure key marketing success metrics, analyze customer acquisition and retention, and build a culture of developing and testing hypotheses through experimentation. You've worked in cultures of excellence in the past, and are eager to apply that experience to building robust and scalable marketing analytics systems and processes as our company goes through a phase of rapid growth. Responsibilities : Deep dive into marketing performance data to provide insights to marketing leaders and influence the company's marketing strategy Define core marketing metrics that measure the team's success. Set goals, monitor performance, and develop actionable reporting for campaigns and channels Identify and size opportunities to improve marketing effectiveness, influencing marketing roadmap through your insights and recommendations on audience targeting, channel optimization, and messaging effectiveness Develop hypotheses on marketing initiatives, design experiments or causal inference studies, analyze the results, and make recommendations based on impact to key metrics Build a data-driven marketing culture from the ground up by establishing foundational marketing analytics best practices and making marketing data more accessible across the company You might be a good fit if you have: 6+ years of experience in data science or analytics roles, preferably in a marketing or customer acquisition context 3+ years of experience deeply embedded in Marketing teams, turning marketing data into concise and insightful analysis that drives business outcomes Experienced in measuring different types of marketing activities, have a holistic view of how different programs are supporting each other (e.g. brand growth, consumer enterprise) Solid technical skills in experimentation and causal inference to measure the incrementality of the spend; Experience in building user segmentation to inform marketing strategies A passion for the company's mission of building helpful, honest, and harmless AI Expertise in Python, SQL, and marketing analytics platforms and visualization tools Familiarity with both B2C and B2B/Enterprise marketing analytics A bias for action and urgency, not letting perfect be the enemy of the effective A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress A deep curiosity and energy for pulling the thread on hard questions about customer behavior and marketing performance Highly effective written communication and presentation skills, with ability to translate complex analyses into actionable marketing insights 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: $275,000 $370,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be i ... (truncated, view full listing at source)
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