# Sr. Security Data Scientist

**Company:** [Illumio](https://hotfix.jobs/companies/illumio)
**Location:** Sunnyvale, CA
**Role:** Data Science
**Salary:** $170k – $196k/yr
**Experience:** 5+ years
**Skills:** Python, pandas, NumPy, scikit-learn, TensorFlow, PyTorch, SQL, Machine Learning, Mitre Att&Ck, Graph Neural Networks, Neo4J, AWS, GCP, Kubernetes, Anomaly Detection
**Posted:** 2026-05-12

> Develops ML models for threat detection, risk assessment, and anomaly detection using security graphs and telemetry data. Collaborates with product teams to integrate insights into cybersecurity platform features. Requires 5+ years in security data science with Python/ML expertise.

## Job Description

## Your Impact

### Threat Intelligence and Risk Modeling
- 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.

### Detection and Analytics Engineering
- 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.

### Product Collaboration and Strategic Guidance
- 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.

### Research and Thought Leadership
- 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.

## Your Toolkit
- 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.
- Familiarity with threat detection principles and frameworks (e.g., MITRE ATT&CK).
- Security telemetry sources (e.g., EDR, NDR, AWS or Azure flow logs, AWS GuardDuty, Azure Defender data, etc).
- Network security fundamentals, including zero-trust and segmentation concepts.
- Proven ability to evaluate models, tune parameters, and manage challenges like imbalanced data in security scenarios.
- Skill in communicating technical insights to diverse audiences, from engineers to product leaders.
- Experience with large-scale telemetry datasets from varied sources.

**Preferred Qualifications**
- 7-10+ years in the field, with a track record in high-impact security roles.
- Knowledge of graph databases and analytics (e.g., Neo4j, graph algorithms applied to security).
- Experience productionizing ML models in cloud environments (e.g., AWS, GCP, Kubernetes).
- Background at a cybersecurity product company (e.g., in endpoint, SIEM, or network security).
- Expertise in identity threats or integrating threat intel APIs.
- Publications, open-source contributions, or certifications (e.g., CISSP, GIAC, advanced ML certs).

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