Founding Applied Data Scientist

ABOUT OUTTAKE Outtake exists to empower and facilitate trust for a digital-first world. Today, impersonation, fraud, AI-driven scams, and identity abuse spread faster than any security team can respond to. So we built something different: an agentic AI platform that proactively detects, monitors, and takes down impersonators, automating protection in hours, not weeks. Built by ex-Palantir, ex-CTO/founders, and ex-Notion engineers, Outtake is designed for clarity, autonomy, and velocity. Our goal is ambitious: become the trust layer of the modern internet. And we intend to do it with a lean, dense, exceptionally talented team. Outtake is backed by top-tier investors and operators who believe in our mission and our model. With strong financial footing and a long runway, we prioritize creating an environment where people can do the best work of their careers. ABOUT THE ROLE We’re looking for a Founding Applied Data Scientist to define how Outtake understands, measures, and improves the performance of our product, business, and AI systems. At a high level, this person will build the data foundation that turns messy product usage, customer outcomes, model behavior, and business operations into clear decisions and durable systems. Our product operates in a noisy, adversarial, fast-moving threat landscape. We need to know what is working, where our agents are succeeding or failing, how customers are experiencing value, and how the business should price, package, and prioritize our work. Data is how we make those questions legible. This role is for someone who is equally comfortable building pipelines, defining metrics, writing SQL, partnering with product and finance, and reasoning about AI evals. You should be excited to operate at the intersection of analytics engineering, applied data science, product strategy, and AI systems evaluation. We are early, so this is not a narrow reporting or dashboarding role. You will shape the semantic layer, define canonical metrics, bui