Investigate FP/FN and product escalations from PS and SOCC related to BMP and Account Protector.
Perform deep-dive analysis on traffic patterns, request signatures, behavioral signals, and telemetry to identify root causes.
Develop and validate targeted fixes — rule tuning, threshold adjustments, feature engineering — and communicate findings clearly to teams.
Analyze trends across case history to identify recurring FP/FN patterns and systemic gaps in detection coverage.
Author well-scoped, well-documented research tickets for novel or unresolved issues, providing sufficient context to accelerate resolution by the expert-DS team.
Serve as the technical bridge between PS/SOCC operations and the core data science research group — translating operational case data into actionable research signals.
Requirements
2–5 years of experience in data science or applied analytics within a production environment
Strong proficiency in Python for data analysis and solid SQL skills for querying and analyzing large-scale event and telemetry datasets.
Hands-on experience in web and application security, including bot detection, credential stuffing, account takeover (ATO), fraud, and other forms of automated abuse.
Proven experience working with commercial bot mitigation, fraud detection, risk management, or application security platforms, including tools such as WAFs and bot detection solutions.
Solid understanding of Internet protocols such as TCP/IP, HTTP/S, DNS, and TLS/SSL, including how they are used and exploited in automated attack methods.
Experience analyzing multi-dimensional threat signals, including behavioral biometrics, device fingerprinting, IP intelligence, session behavior, and request patterns
Strong written and verbal communication skills, with the ability to clearly present complex findings to both technical and non-technical audiences