Cyber Security Data Science

Orcapod Consulting Services; Hyderabad; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Orcapod Consulting Services in Hyderabad, India, seeks a Security Data Scientist with 7–12 years overall experience and 3+ years applying ML, graph analytics, or data engineering to cybersecurity/fraud domains. You will work with UEBA, anomaly detection, and security knowledge graphs to detect threats.

Responsibilities include building scalable ML models, graphs, and ETL pipelines across multi-cloud logs, while exploring GraphRAG and LLM-based retrieval.

Qualifications

• Experience applying ML, graph analytics, or data engineering to cybersecurity/fraud domains.
• Proficient with security knowledge graphs and graph databases.
• Hands-on development of ML models for threat detection and security analytics.

Responsibilities

• Build and deploy ML models for cybersecurity threat detection.
• Develop security knowledge graphs connecting identities, assets, permissions, vulnerabilities, and attack paths.
• Perform graph analytics to detect hidden relationships and assess security risks.
• Build scalable ETL/ELT pipelines for multi-cloud security logs and telemetry.
• Apply anomaly detection and link prediction to identify suspicious activities.
• Integrate threat intelligence and security frameworks into analytical models.
• Explore GraphRAG and LLM-based knowledge graph retrieval solutions.

Skills

Security Data Science

UEBA

Anomaly detection

Threat scoring

Graph analytics

Tools

Neo4j

Amazon Neptune

Azure Cosmos DB

Memgraph

Cypher

Gremlin

SPARQL

BigQuery

Apache Spark

GCP

Azure Synapse

Databricks

Kafka

Scikit-Learn

PyTorch

TensorFlow

Pandas

NumPy

NetworkX

Pyvis

MITRE ATT&CK

STIX/TAXII

Cloud security

Job description

Job Description Summary Security Data Scientist

Role: Security Data Scientist Experience: 7–12 years overall Relevant Experience: 3+ years applying ML, graph analytics, or data engineering to cybersecurity/fraud domains.

1. Mandatory Skills

• Cybersecurity Data Science: UEBA, insider threat detection, anomaly detection, threat scoring.
• Machine Learning: Scikit-Learn, PyTorch / TensorFlow.
• Security Knowledge Graphs: Neo4j, Amazon Neptune, Azure Cosmos DB, Memgraph.
• Graph Analytics: Link analysis, attack path analysis, PageRank, centrality, community detection, link prediction, GNNs.
• Graph Query Languages: Cypher, Gremlin, SPARQL.
• Data Engineering: BigQuery, Apache Spark, GCP, Azure Synapse, Databricks, Kafka.
• Python: Pandas, NumPy, NetworkX, Pyvis.
• Security Domain: SIEM/SOC analytics, security telemetry, MITRE ATT&CK, STIX/TAXII, cloud security.

2. Key Responsibilities

• Build and deploy ML models for cybersecurity threat detection.
• Develop security knowledge graphs connecting identities, assets, permissions, vulnerabilities, and attack paths.
• Perform graph analytics to detect hidden relationships and assess security risks.
• Build scalable ETL/ELT pipelines for multi-cloud security logs and telemetry.
• Apply anomaly detection and link prediction to identify suspicious activities.
• Integrate threat intelligence and security frameworks into analytical models.
• Explore GraphRAG and LLM-based knowledge graph retrieval solutions.