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HUMAN's Detection team protects the internet by disrupting the economics of cybercrime. The Threat Research Analyst role focuses on identifying bot traffic masquerading as human ad viewers, understanding how bad actors monetize invalid traffic, and launching mitigations to stop them.
You will manage the full cycle of fraud fighting: from exploratory research through development and deployment of statistical detection techniques. Key responsibilities include identifying novel detection methodologies for 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 fraud actor behavior; collaborating with Product and Engineering to deliver customer-facing features; and constructing complex SQL queries and analytical notebooks to analyze historical data at scale (TB to PB).
You'll participate in weekly triage rotations as the first line of analysis for customer and internal fraud efficacy inquiries, continuously identify process and product improvements to accelerate threat identification and response, and rigorously document research and mitigations for visibility and auditability. The role emphasizes experimentation—testing new threat identification methods, emerging tools, and novel approaches.
Ideal candidates demonstrate strong ownership mentality, curiosity about fraud patterns and adversarial thinking, collaborative communication skills, and proficiency in performant SQL (Snowflake experience is a plus). Python experience and AdTech exposure are preferred. You thrive on solving complex puzzles, meticulous experimentation, and staying ahead of fraudsters.
