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 aligning our marketing programs to benefit our customers, users and society. In this unique company, technology, and moment in history, your work will be critical to informing our marketing and personalization strategy 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 success metrics and measurement approaches for our lifecycle and personalization efforts. 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 as our company continues through a period of rapid growth and evolution. Responsibilities: - Partner closely with marketing, product and commercial teams to understand our products and underlying user needs - Establish north star metrics and guardrails to understand the effectiveness of different marketing interventions - Develop a feedback approach which enables continuous learning and improvement for the teams operating in different marketing categories - Identify 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 ML role, preferably in a marketing or customer acquisition context - 3+ years of experience deeply embedding in Marketing teams, turning marketing data into concise and insightful systems that drive business outcomes - A passion for the company's mission of building helpful, honest, and harmless AI - Experience building user segmentation systems to drive marketing campaigns - Experience with the ecosystem of Causal AI and related technologies - A bias for action and urgency, not letting perfect be the enemy of the effective - An ability to thrive and drive clarity in ambiguous, fast-moving environments 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: $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. 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. 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.