AI Cyber Data Scientist

Executive Summary:

The IT HUB AI Cyber Data Science Specialist is responsible for designing, operating and optimizing graph-based data platforms and AI solutions supporting Equans cybersecurity use cases. The role combines Neo4j Aura product ownership, advanced graph algorithms and data structures expertise, agentic AI architecture performance and reliability management, and hands-on integration of data pipelines across the IT ecosystem. Acting as SLS Data SPOC and Group/Innovation/special projects SPOC, the specialist drives end-to-end business cases, from opportunity framing to measurable value delivery.

Role Evolution:

The scope of the IT HUB AI Cyber Data Science Specialist role may evolve with the rapidly evolving environment of AI and Cybersecurity.

Key Missions:

The purpose of the IT HUB AI Cyber Data Science Specialist role is to apply graph-based AI techniques (with a focus on Neo4j Aura) to support Cybersecurity use cases that require deterministic outputs that genAI only struggles to produce. The role ensures that graph data models provide solid knowledge grounding for agentic AI architectures in the cyber domain.

• Provide product ownership for the Neo4j Aura platform and associated graph services.
• Design and maintain data pipelines and models enabling graph analytics and agentic AI use cases.
• Integrate data pipelines in the graph analytics platform, using ETL or MCP typically.
• Act as SLS Data SPOC for data pipelines integration when business data is involved.
• Promote forward-thinking approaches to AI and data, including demonstrating the value of graph approaches as complimentary to genAI and agentic systems for mission critical applications.

Expected Impact: Deliver high-value AI and graph-based use cases, improve data discoverability and relationships understanding, and create reusable graph and AI assets for Cyber use cases.

Required Profile:

The IT HUB AI Cyber Data Science Specialist combines strong cybersecurity knowledge with a solid understanding of graph platforms and their value in modern Cyber AI use cases. The role requires both technical ability on graph database technologies and cybersecurity knowledge in order to deploy use cases quickly.

Education & Background:

• Master’s degree in Computer Science, Applied Mathematics, Data Science, Engineering or equivalent experience.
• 5+ years in data engineering, data science or software engineering, including experience with graph databases or knowledge graphs; experience in AI/ML or LLM-based solutions is a strong asset.
• Neo4j (Aura preferred), graph modeling and algorithms, data engineering (ETL/ELT, APIs), Python/Java or similar, cloud platforms, LLM integration and tuning, observability and performance optimization.
• Agile / Scrum or Kanban, DevOps / MLOps practices, product ownership basics, documentation and testing culture.
• Professional Experience:
• Prior experience in a data scientist role and cybersecurity.
• Experience working in an international, multi-stakeholder environment.
• Familiarity with secure development lifecycle (SDLC) or MLOps/AI lifecycle practices is a plus.

Skills and Competencies:

A mix of technical skills is required to successfully interface with all data providers and consumers.

• Good understanding of cybersecurity principles, risk management and security controls.
• Technical toolbox for data integration, Python programming, data connectors, ETL scripts, MCP servers…
• Advanced cypher queries to deliver the graph reasoning logic.
• AI/ML experience for specific genAI integrations, such as model post-training on database requests.
• Understanding of the value of graph in the AI ecosystem and designing the right tool for the right use case.

Stakeholders and Collaboration:

The IT HUB AI Cyber Data Science Specialist interacts with multiple stakeholders across Equans and Group-level organizations.

• IT HUB AI & Data teams (data engineers, data scientists, AI architects).
• Cybersecurity teams sponsoring graph/AI use cases.
• Innovation, Group digital and special project teams if needed (Group/Innovation/SPOC role).
• Vendor and partner contacts for Neo4j Aura, cloud and AI services.

Success criteria and KPIs:

Success in the IT HUB AI Cyber Data Science Specialist role is measured through both qualitative and quantitative indicators reflecting value for Cyber.

• Positive feedback from Cyber AI Lab, GRC, Legal and local AI teams regarding support and collaboration.
• Reliability and ROI of solutions deployed, including data ecosystem, graph and AI consumption, stability and predictability of systems in production.