The Account Defender team at HUMAN is responsible for safeguarding user accounts across the internet by identifying and mitigating fraudulent activities post-login, including synthetic account creation, unauthorized account access (ATO), and coordinated malicious behavior.

We combine large-scale behavioral data with detection logic to stop sophisticated actors and protect real users.

We’re looking for a Senior Data Scientist to join our team and take a key role in shaping detection strategies, researching behavioral signals, and developing models that power HUMAN’s real-time fraud defenses.

This is a high-impact role that involves working closely with other researchers, data analysts, product managers, and engineers to build, deploy, and iterate on fraud detection capabilities at scale.

What you’ll do:

• Lead end-to-end research projects to detect fake users and account takeovers – from exploring behavioral patterns and validating hypotheses to deploying logic in production and evaluating impact.
• Design and implement detection logic and features based on large-scale behavioral signals and fraud patterns.
• Analyze real-world traffic to surface anomalies and iterate on detection strategies that improve precision and coverage.
• Work closely with Product and Engineering to integrate solutions into production systems and influence roadmap decisions.
• Help shape the team’s detection methodologies, tooling, and best practices for scalable, real-time fraud mitigation.

Who you are:

• You have experience solving large-scale, data-intensive problems in production environments (we process trillions of events per day, so comfort with big data is essential).
• You are fluent in Python and SQL, and comfortable with modern data tools and platforms.
• You understand the strengths and trade-offs of various statistical and detection approaches, and can ship practical solutions to production.
• You are able to bring clarity to ambiguous problems and simplicity to complex ones.
• You write maintainable, object-oriented code and have strong debugging skills.
• You’ve worked on cross-functional projects with both technical and non-technical stakeholders, and are comfortable following SDLC best practices (version control, unit testing, CI/CD).
• Experience in fraud detection, account security, or the cybersecurity space is a strong advantage