Infoplus Technologies UK Limited
Security Data Scientist
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Lead Data Scientist
We are seeking a Lead Data Scientist to design, engineer, and operationalize enterprise Security Knowledge Graphs. This role combines data science, graph engineering, cybersecurity analytics, and technical leadership to enable attack-path analysis, threat investigation, exposure prioritization, GraphRAG, and AI-assisted security operations.
Key Responsibilities
- Architect and implement Security Knowledge Graphs, including ontology, taxonomy, entity/relationship models, and lifecycle standards.
- Build production-grade ingestion pipelines from SIEM, EDR/XDR, IAM/PAM, vulnerability scanners, cloud security platforms, and threat intelligence feeds.
- Develop entity extraction, identity resolution, schema mapping, relationship inference, and graph enrichment capabilities.
- Apply graph analytics for attack paths, privilege escalation, lateral movement, toxic combinations, and vulnerability prioritization.
- Design and evaluate graph algorithms and ML models (centrality, clustering, anomaly detection, embeddings, GNNs).
- Implement GraphRAG and knowledge-grounded assistants that combine graph traversal, vector retrieval, structured evidence, and LLM reasoning.
- Partner with SOC, threat intelligence, IAM, vulnerability management, and cloud security teams to deliver reusable graph-powered capabilities.
- Mentor engineers and data scientists while leading technical reviews, coding standards, and production-readiness gates.
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Required Skills & Experience
- Knowledge Graphs: Ontology design, RDF/property graphs, Neo4j (deep expertise), plus one additional graph platform (TigerGraph, Neptune, Cosmos DB Gremlin, JanusGraph, ArangoDB).
- Graph Data Science: Neo4j GDS, NetworkX, PyTorch Geometric/DGL; embeddings, link prediction, anomaly detection, GNNs.
- Programming & Engineering: Advanced Python, SQL, APIs, CI/CD, containers, distributed processing, debugging, performance optimization.
- Data Engineering: Spark/Databricks, Kafka, ETL/ELT pipelines, scalable cloud storage.
- Cybersecurity: SOC workflows, threat hunting, IAM/PAM, Zero Trust, vulnerability management, cloud security.
- Security Standards: MITRE ATT&CK, STIX/TAXII, CVE, CWE, NIST, CIS Controls.
- GenAI & GraphRAG: LLM-based extraction, retrieval orchestration, grounding, explainability, guardrails.
- MLOps & Observability: Model deployment, monitoring, drift detection, auditability.
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Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, AI, Cybersecurity, or related field.
- Proven ownership of at least one production knowledge graph or graph analytics solution.
- Strong portfolio of Python and graph-query development, data pipeline engineering, and production deployment.
- Excellent communication, mentoring, and cross-functional leadership skills.
Preferred
- Experience with cloud-native security/data services (Azure, AWS, GCP).
- Certifications such as CISSP, CISM, GIAC, cloud security, or Neo4j Graph Data Science (advantageous but not mandatory).
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