The Account Defender team at our company 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.
Were 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 our companys 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 teams detection methodologies, tooling, and best practices for scalable, real-time fraud mitigation.
We combine large-scale behavioral data with detection logic to stop sophisticated actors and protect real users.
Were 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 our companys 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 teams detection methodologies, tooling, and best practices for scalable, real-time fraud mitigation.
Requirements:
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.
Youve 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.
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.
Youve 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.
This position is open to all candidates.
