about 3 hours ago
Responsibilities
- Design, build, and maintain machine learning models for anomaly detection.
- Operationalize models and detections from notebook to production.
- Engineer and tune features from various telemetry sources.
- Partner with the SOC to triage and improve detection feedback loops.
- Collaborate with stakeholders to translate threat scenarios into analytics.
- Establish model governance and monitor data quality.
- Participate in post-incident reviews to identify new signals.
- Contribute to documentation and standards for the ML detection platform.
- Mentor engineers and analysts on applied ML and anomaly detection.
Requirements
- 7+ years of experience building and operating machine learning models for detection.
- Hands-on experience with data lake and big-data technologies.
- Strong programming skills in Python and SQL.
- Solid understanding of security telemetry sources.
- Working knowledge of anomaly detection techniques.
- Familiarity with security frameworks and adversary tradecraft.
- Experience collaborating with SOC and fraud teams.
- Ability to balance detection coverage and operational load.
- Bachelor’s degree in a related field or equivalent experience.
Tech Stack
Apache FlinkApache KafkaApache SparkAWSAzureDatabricksGoogle Cloud PlatformPandasPythonPyTorchscikit-learnSnowflakeSQLTensorFlow