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Graph Anomaly Detection Jobs in California (NOW HIRING)

Illumio

Sr. Security Data Scientist

Sunnyvale, CA · On-site

$170K - $196K/yr

This graph enables essential functions such as breach risk detection, network segmentation ... Create ML models for anomaly detection, behavioral profiling, and breach identification across ...

CB Smart Recruit

Senior AI/ML Engineer

Los Angeles, CA

$180K - $350K/yr

Composite risk and threat scoring * Long-term anomaly detection * Design ensemble architectures ... Data Fusion & Knowledge Graph Engineering * Design large-scale ingestion pipelines processing:

Plaid Inc

Senior Fraud Research Analyst

San Francisco, CA · On-site

$139K - $191K/yr

Experiment with network/graph analysis, sequence mining, anomaly detection, and custom heuristics where off-the-shelf approaches fail Ecosystem Monitoring & Knowledge Leadership * Continuously survey ...

Cisco

Applied AI Scientist

San Diego, CA

Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting ...

Cisco

Applied AI Scientist

Roseville, CA

Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting ...

Cisco

Applied AI Scientist

Carlsbad, CA

Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting ...

Cisco

Applied AI Scientist

Santa Monica, CA

Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting ...

Cisco

Applied AI Scientist

Irvine, CA

Advanced Anomaly Detection with Graph: Track record developing hybrid graph-temporal approaches (e.g., GNN + Transformer, graph contrastive learning, dynamic graph forecasting) for detecting ...

Walmart

(USA)Staff, Data Scientist

Sunnyvale, CA · On-site

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Sunnyvale, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Mountain View, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Fremont, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Milpitas, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

San Jose, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

San Mateo, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Hayward, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

Walmart

(USA)Staff, Data Scientist

Cupertino, CA · On-site

$143K - $286K/yr

Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs ... outliers, anomaly detection, and regime changes. * Hands-on experience with deep learning ...

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All JobsGraph Anomaly Detection JobsGraph Anomaly Detection Jobs in California

Graph Anomaly Detection information

What are common challenges faced by professionals working in Graph Anomaly Detection, and how can they be addressed?

Professionals in Graph Anomaly Detection often face challenges such as handling large-scale, high-dimensional graph data and distinguishing between legitimate anomalies and noise. Collaborating closely with data engineers and domain experts is essential to ensure accurate labeling and effective feature engineering. Additionally, staying updated with rapidly evolving algorithms and tools is important for optimizing detection performance. Regular cross-functional meetings and ongoing training can help address these challenges and support continuous improvement.

What are the key skills and qualifications needed to thrive in Graph Anomaly Detection, and why are they important?

To excel in Graph Anomaly Detection, you need strong skills in data science, graph theory, and machine learning, typically supported by a degree in computer science or a related field. Proficiency with Python, libraries like NetworkX or PyTorch Geometric, and familiarity with graph databases such as Neo4j are commonly required. Analytical thinking, problem-solving abilities, and attention to detail help professionals identify subtle anomalies and communicate findings effectively. These skills ensure accurate detection of unusual patterns, supporting cybersecurity, fraud prevention, and other critical applications.

What is graph anomaly detection?

Graph anomaly detection is the process of identifying unusual patterns, nodes, edges, or substructures within graph data that deviate from expected behavior. These anomalies could indicate fraud, security breaches, network failures, or other significant events in applications such as cybersecurity, social networks, and financial transactions. Techniques in graph anomaly detection leverage statistical, machine learning, and deep learning approaches to analyze complex relationships and structures within graph data. Detecting these anomalies helps organizations quickly address potential threats or irregularities. The field is interdisciplinary, combining knowledge from data science, graph theory, and domain-specific expertise.

What is the difference between Graph Anomaly Detection vs Data Scientist?

AspectGraph Anomaly DetectionData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of graph theory and machine learningDegree in Statistics, Computer Science, or related fields; proficiency in programming and data analysis
Work EnvironmentResearch labs, tech companies, industries analyzing network dataBusiness, finance, tech firms analyzing large datasets for insights
Industry UsageSpecialized in detecting irregularities in graph-structured dataBroadly used for data analysis, predictive modeling, and decision-making

While both roles involve data analysis and machine learning, Graph Anomaly Detection focuses specifically on identifying irregularities within graph-structured data, whereas Data Scientists work across various data types and analytical tasks. Understanding these differences helps organizations choose the right expertise for their data challenges.

What are popular job titles related to Graph Anomaly Detection jobs in California? For Graph Anomaly Detection jobs in California, the most frequently searched job titles are:
What job categories do people searching Graph Anomaly Detection jobs in California look for? The top searched job categories for Graph Anomaly Detection jobs in California are:
What cities in California are hiring for Graph Anomaly Detection jobs? Cities in California with the most Graph Anomaly Detection job openings:
Graph Anomaly Detection jobs near you
Infographic showing various Graph Anomaly Detection job openings in California as of July 2026, with employment types broken down into 2% As Needed, 89% Full Time, 6% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.
Sr. Security Data Scientist

Sr. Security Data Scientist

Illumio

Sunnyvale, CA • On-site

$170K - $196K/yr

Full-time

Posted 14 days ago

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.
  • 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).
    Bonus Points
  • 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.
    Who You Are
  • A data-driven thinker who excels in ambiguous settings and tests hypotheses rigorously.
  • Passionate about cybersecurity, with a pragmatic approach to balancing detection accuracy and usability.
  • Collaborative, influential, and results-oriented, focused on delivering tangible value to protect customers.
  • Committed to ethical practices in AI and eager to thrive in a vibrant, talent-rich environment.

#LI-PO1 #LI-ONSITE
Our Commitment
Illumio believes that an environment of unique backgrounds, experiences, viewpoints, and individual contributions creates a culture of belonging, drives our future, and makes us stronger together in support of our customers and their success.
All official job offers from our company are extended directly by our recruitment team and will be sent through an official E-Signature document for your review and signature. Please be aware that we do not ask for any personal information in the process of extending offers of employment, such as financial details or social security numbers. Upon acceptance of any offer, we will request such information as part of the onboarding process prior to or on your first day of employment, and only after completing a background check through an authorized third-party vendor. If you receive any communication asking for personal details outside of these processes, please contact us immediately to verify the authenticity of the request. Your security is important to us, and we are committed to a safe and transparent hiring experience.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Illumio will consider for employment qualified applicants with arrest and conviction records.

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