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HUMAN (formerly clean.io) is a cybersecurity company protecting the internet by disrupting the economics of cybercrime. The Detection team's Threat Research function identifies bot traffic masquerading as human ad viewers, understands monetization tactics of bad actors, and deploys mitigations to stop them.
In this role, you will manage the full cycle of fraud fighting from exploratory research through statistical detection technique development and deployment. Key responsibilities include: identifying novel methodologies to detect invalid and bot traffic; deploying rapid stop-gap mitigations for emerging threats; building robust defenses using statistical analysis of supply chain data, network signals, and JS behavior; collaborating with Product and Engineering on customer-facing features; writing complex SQL queries and analytical notebooks on TB-to-PB scale datasets; participating in weekly triage rotations to analyze customer and internal fraud efficacy inquiries; documenting research and threat mitigations for auditability; and continuously experimenting with new threat detection methods and tooling.
You are detail-oriented with strong ownership mentality, driven to improve processes and quality. You think strategically about fraudster tactics and enjoy solving complex puzzles through meticulous experimentation. You collaborate transparently across teams and communicate findings clearly. You have proficiency in performant SQL (Snowflake experience a plus), experience improving analytical processes and implementing tooling, and Python experience or exposure. AdTech or fraud detection background is preferred but not required.
HUMAN was founded with a hacker mindset to make the internet safer. The platform verifies humanity across 20+ trillion interactions weekly for major brands and platforms. The company offers comprehensive total rewards including well-being stipends, learning budgets, flexible work, and dedicated time off. Teams are distributed globally with HQ in NYC.
