Security Data Scientist

An opportunity for a Security Data Scientist to work at the intersection of AI, data science and cybersecurity, using machine learning, statistical analysis and data engineering to solve security problems at scale.

Key Responsibilities

• Build AI and machine learning models to detect anomalous behaviour, insider threats, malware and network intrusions that rule based systems miss
• Develop AI driven user and entity behaviour analytics (UEBA) to baseline normal activity and flag deviations
• Analyse large volumes of threat intelligence data to surface patterns, correlate IOCs and prioritise risk
• Apply machine learning to cut false positives in SIEM and EDR tools so SOC analysts can focus on real threats
• Use graph based security analytics (e.g. Neo4j, Amazon Neptune, Microsoft Security Graph) to map relationships between users, devices, accounts and assets, and spot lateral movement, privilege escalation paths and complex attack chains
• Apply AI powered fraud and anomaly detection to identify unusual transactions and access patterns

What We’re Looking For

• Strong background in data science, machine learning and statistical analysis
• Proven experience applying AI and ML to cybersecurity problems
• Familiarity with SIEM and EDR tooling
• Exposure to graph databases and graph analytics
• Experience in financial services, ideally with fraud or anomaly detection

Location: Hybrid, 3 days per week on site (London, Bristol, Leeds, Halifax or Edinburgh)

Duration: Initially 12 months

Start: ASAP

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