Senior Security Data Scientist

• We’re looking for a talented Security Data Scientist to provide ongoing guidance on threats, threat intelligence, assessment models, and risk modeling
• You’ll detect threats within our data ecosystems, build robust models, and collaborate closely with product teams to shape features, designs, and strategic direction
• This role bridges data science, machine learning, threat research, and product development, offering a unique opportunity to impact how global organizations defend against advanced cyber threats in a high-demand field
• Examine large-scale security datasets to identify threat patterns, attacker TTPs (Tactics, Techniques, and Procedures), and emerging risks
• Construct and iterate on threat risk models using statistical and machine learning methods to evaluate breach likelihoods and segmentation efficacy
• Utilize security graphs to model attack paths, recommend segmentation strategies to reduce the risk of lateral movement, and suggest mitigation strategies
• Create ML models for anomaly detection, behavioral profiling, and breach identification across multi-cloud, hybrid, and on-premises setups
• Work with threat researchers and engineers to enhance datasets, test hypotheses, and develop detection algorithms based on real-world threats
• Assess and refine model performance to deliver reliable detections with low false positives
• Team up with product managers, engineers, and designers to integrate threat insights into roadmaps, user interfaces, and analytics tools
• Advise on threat assessment frameworks, data needs, and incorporating external
• Intelligence sources.Deploy and monitor models in production, ensuring scalability and reliability
• Investigate cutting-edge techniques for graph-based threat detection, like graph neural networks or AI-optimized policies
• Contribute to internal research, patents, and potential publications to position Illumio as an industry leader
• Track adversary trends, regulatory shifts, and innovations to influence our detection and risk strategies

### Benefits

• Health and Dependent Savings Accounts
• Life and Disability Programs
• Paid Parental Leave
• Voluntary Benefit Programs
• Company Sponsored Wellness Program
• Wellness Reimbursement Program
• Retirement Savings
• Equity Opportunities
• Paid time off and Paid Holidays
• Employee Incentive Program
• Medical, Dental, Vision Coverage- 5+ years of experience in data science, detection engineering, threat intelligence, or security analytics, ideally in dynamic environments like cloud or network security
• Proficiency in Python for data handling and modeling (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), complemented by solid SQL skills for large dataset queries
• Hands-on experience developing and deploying ML or statistical models for security applications, such as anomaly detection or risk assessment
• Preferred Qualifications
• Threat detection principles and frameworks (e.g., MITRE ATT&CK)
• Experience productionizing ML models in cloud environments (e.g., AWS, GCP, Kubernetes)
• Skill in communicating technical insights to diverse audiences, from engineers to product leaders
• Experience with large-scale telemetry datasets from varied sources
• Knowledge of graph databases and analytics (e.g., Neo4j, graph algorithms applied to security)
• Network security fundamentals, including zero-trust and segmentation concepts
• 7-10+ years in the field, with a track record in high-impact security roles
• Security telemetry sources (e.g., EDR, NDR, AWS or Azure flow logs, AWS GuardDuty, Azure Defender data, etc)
• Proven ability to evaluate models, tune parameters, and manage challenges like imbalanced data in security scenarios
• Background at a cybersecurity product company (e.g., in endpoint, SIEM, or network security)
• Expertise in identity threats or integrating threat intel APIs
• Familiarity with Bay Area cybersecurity ecosystems or prior work in tech hubs
• Publications, open-source contributions, or certifications (e.g., CISSP, GIAC, advanced ML certs)
• Committed to ethical practices in AI and eager to thrive in a vibrant, talent-rich environment
• Collaborative, influential, and results-oriented, focused on delivering tangible value to protect customers
• Passionate about cybersecurity, with a pragmatic approach to balancing detection accuracy and usability
• A data-driven thinker who excels in ambiguous settings and tests hypotheses rigorously