Applied Data Scientist
Posted 28 Jul 2026
Advertised as “Founding Applied Data Scientist”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- People management
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
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.
The Role
This is a Founding Applied Data Scientist role. You will define how Outtake understands, measures, and improves the performance of our product, business, and AI systems, building 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. You will make legible what is working, where our agents are succeeding or failing, how customers are experiencing value, and how the business should price, package, and prioritize its work. The role begins as an individual contributor position; the desire to eventually hire, mentor, and scale a high-performing data function will be valuable as the function grows.
This is not a narrow reporting or dashboarding role. You will shape the semantic layer, define canonical metrics, build the analytical infrastructure, influence product and pricing decisions, and set the long-term bar for how Outtake uses data as the company scales — operating comfortably at the intersection of analytics engineering, applied data science, product strategy, and AI systems evaluation.
What You’ll Do
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Own our analytical data pipeline and infrastructure across product, business, and AI performance data.
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Build and own the long-term roadmap for data infrastructure, analytics, and applied data science at Outtake.
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Define and maintain the semantic layer in our product analytics stack, including Hex and the underlying warehouse models.
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Build canonical performance metrics for our product and business, including activation, usage, retention, customer value, operational efficiency, and agent effectiveness.