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Cloudflare is seeking a Principal Data Scientist to lead detection research and strategy within its Detection department, which identifies automated, fraudulent, and malicious activity across Internet-scale data. This is a high-impact role at the heart of Cloudflare's mission to protect and accelerate Internet applications.
Key responsibilities include leading research, design, and evaluation of detection models that identify fraud, abuse, and bot activity at scale. You will mentor other data scientists in uncovering patterns that distinguish adversaries from legitimate users, and own the detection measurement framework—defining metrics and evaluation strategies for problems where ground truth is noisy, delayed, or contested. You'll drive adoption of promising AI/ML techniques, represent Cloudflare in the broader research community, and shape long-term detection strategy by identifying gaps and opportunities across multiple product areas.
You will drive cross-functional partnerships with ML Engineers, Data Engineers, and Product teams, influencing roadmaps and aligning detection strategy with company priorities. This role requires deep expertise in fraud and bot detection at scale, with solid applied statistics, machine learning, and AI methodology fundamentals. You should be fluent with large-scale data, comfortable with Python and SQL in production environments, and have demonstrated ability to make high-stakes technical decisions with incomplete information.
Ideal candidates have 8–10+ years of professional experience in Data Science, ML Engineering, or Software Engineering, with a track record of building detections when ground truth is scarce, weak, delayed, or absent. You thrive in adversarial environments where threat actors actively fight back against your models. This is a principal-level individual contributor role with significant influence over company detection strategy and cross-functional technical direction.
