Illumio

cybersecurity

Sr.SecurityDataScientist

$170–196k Sunnyvale, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr. Security Data Scientist at Illumio. Skills: Security Data Science, Threat Intelligence, Risk Modeling, Machine Learning, Statistical Modeling, Detection Engineering. 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”

Industry & Context.

cybersecurity
Problems you'll solve

data-driven thinker who excels in ambiguous settings and tests hypotheses rigorously

Eligibility Requirements

4 ON-SITE DAYS A WEEK IN SUNNYVALE, CA HEADQUARTERS

What They're Looking For.

Must Have

5+ years of experience in data science, detection engineering, threat intelligence, or security analytics, Proficiency in Python for data handling and modeling (e. g. , Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), 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), Familiarity with Security telemetry sources (e. g. , EDR, NDR, AWS or Azure flow logs, AWS GuardDuty, Azure Defender data, etc), Familiarity with 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

Nice to Have

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), Familiarity with Bay Area cybersecurity ecosystems or prior work in tech hubs

What You'll Do.

Examine large-scale security datasets to identify threat patterns

attacker TTPs (Tactics

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

and breach identification across multi-cloud

and on-premises setups

Work with threat researchers and engineers to enhance datasets

and develop detection algorithms based on real-world threats

Assess and refine model performance to deliver reliable detections with low false positives

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

and potential publications

Track adversary trends

and innovations to influence our detection and risk strategies

How You'll Work.

Team & Collaboration

collaborate closely with product teams to shape features, designs, and strategic direction; 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; Work with threat researchers and engineers to enhance datasets, test hypotheses, and develop detection algorithms

Communication Scope

Skill in communicating technical insights to diverse audiences, from engineers to product leaders

Full Job Description

ONWARDS TOGETHER! Illumio is the leader in ransomware and breach containment, redefining how organizations contain cyberattacks and enable operational resilience. Powered by the Illumio AI Security Graph, our breach containment platform identifies and contains threats across hybrid multi-cloud environments – stopping the spread of attacks before they become disasters. Recognized as a Leader in the Forrester Wave™ for Microsegmentation, Illumio enables Zero Trust, strengthening cyber resilience for the infrastructure, systems, and organizations that keep the world running. LOCATION: 4 ON-SITE DAYS A WEEK IN SUNNYVALE, CA HEADQUARTERS. OUR TEAM'S VISION: At Illumio, we’re pioneering cybersecurity innovation with our Illumio Insights platform, which leverages a dynamic security graph built from network flows, workload inventories, identity data, threat data, and vulnerability data. This graph enables essential functions such as breach risk detection, network segmentation assessment, active breach identification, and intelligent policy recommendations. To accelerate our product evolution, we’re expanding our Threat Research Team with a dedicated expert who will serve as a long-term subject matter expert (SME) for the Illumio Insights product team. 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. 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. - Con

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