Description: Role: Security Data Scientist

Required Technical Skill Set: Cyber Security Data Science, Security Knowledge Graphs (Graph Databases, Ontologies & Link Analysis), Data Engineering (Big Query, Spark, GCP / Azure Data Pipelines), Machine Learning & Anomaly Detection, Attack Path Analysis, Python (Pandas, PyTorch, Scikit-Learn, NetworkX), Graph Query Languages (Cypher / Gremlin / SPARQL), Security Telemetry & SIEM/SOC Analytics

Experience Range: 7 – 12 Years overall
Location: Hyderabad
technical/data science experience (with 3+ years applying machine learning, graph analytics, or data engineering to cyber security/fraud domains)

Must-Have (Candidates must demonstrate depth in core areas and a blend/combination of the following specialisms)
• Cyber Security Data Science & ML: Proven experience designing, training, and deploying machine learning models specifically for security use cases (e.g., UEBA, insider threat detection, anomalous authentication patterns, network intrusion, automated threat scoring).
• Security Knowledge Graphs & Graph Analytics: Hands-on experience modeling and querying complex security relationships (identities, assets, permissions, attack paths, vulnerabilities) using Graph Databases (Neo4j, Amazon Neptune, Azure Cosmos DB / Gremlin, AWS Neptune, or Memgraph) and graph traversal languages (Cypher, Gremlin, SPARQL).
• Graph Machine Learning & Link Analysis: Practical knowledge of graph algorithms (centrality, community detection, shortest path,



Page Rank) and Graph Neural Networks (GNNs) or link prediction to uncover hidden relationships and blast radiuses across enterprise security assets.
• Data Engineering & Big Data Pipelines: Robust data engineering expertise in designing scalable ETL/ELT pipelines to ingest, normalize, and enrich massive volumes of multi-cloud security telemetry and logs using GCP Big Query / Dataproc, Azure Synapse / Databricks, Apache Spark, or Kafka.
• Programming & Data Science Toolkit: Advanced proficiency in Python and standard data science libraries (Pandas, Num Py, Scikit-Learn, PyTorch / Tensor Flow, NetworkX, Pyvis, DGL/PyG).
• Security Domain Knowledge: Solid understanding of cyber security frameworks, threat intelligence feeds (MITRE Telecommunication&CK;, STIX/TAXII), identity access graphs, and cloud asset topologies.

Good-to-Have
• Experience with GenAI / LLM-powered knowledge graph retrieval (GraphRAG, Vector + Graph hybrid indexing, Lang Chain / Llama Index).
• Familiarity with Data Security Posture Management (DSPM), Cloud Security Posture (CSPM), or asset inventory discovery tools.
• Experience working in regulated financial services environments handling sensitive customer and transactional data.
• Relevant certifications in Data Science, Cloud Data Engineering (GCP Professional Data Engineer, Azure Data Scientist / Data Engineer), or Cyber Security (CISSP, GDAT, or equivalent).

📌 IND_Senior Security Engineer (India)
🏢 Artech Infosystems
📍 India