Senior Data Scientist, Detection

Responsibilities

• Research, design, and evaluate detection models that identify automated, fraudulent, and malicious activity across Internet-scale data.
• Dig into massive datasets to uncover the patterns and behaviors that distinguish adversaries from legitimate users.
• Define how detection success is measured, designing metrics and evaluation strategies for problems where ground truth is noisy, delayed, or contested.
• Stay current on emerging AI/ML research and evaluate how new techniques (e.g., LLMs, generative AI) can be applied to our products.
• Partner with ML Engineers, Data Engineers, and Product to take detection approaches from research to production and measure their real-world impact.

Requirements

• Experience across fraud, abuse, and/or bot detection on large, high-velocity traffic.
• Strong fundamentals in applied statistics, machine learning, and AI methodology; choose the right technique for the problem and fluency with large-scale data.
• At least 5-7 years of experience professionally working in Data Science, ML Engineering, or Software Engineering.
• Very comfortable with Python & SQL in production environments.

Nice-to-Haves

• At home in ground truth ambiguity: make real progress with weak, delayed, or absent labels and energized by adversaries that fight back.
• Understand (or are curious to learn) how to act on detections without tipping your hand, knowing that how you deploy and respond can erode your future visibility.
• Pragmatic about complexity: know when a simple solution beats a complex one, and don't chase small gains at disproportionate cost.
• Disciplined in code: apply strong programming and engineering best practices in both research and production code.
• Impact-driven and clear: connect your work to business impact and communicate clearly across technical and non-technical stakeholders.

Compensation

For New York City based hires: Estimated annual salary of $185,000 - $231,000.