This role combines deep technical expertise with leadership responsibility, driving multidisciplinary Data Science initiatives end-to-end within complex, security policy management systems.
The role drives the development of innovative, production-grade AI capabilities - including security AI agents and advanced machine learning models built on complex security data.
Original thinking, deep technical rigor, intellectual agility, and exceptional problem-solving are essential.
Key Responsibilities
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Lead end-to-end Data Science initiatives from problem framing through validation, CI/CD-based production deployment, monitoring, and ongoing operational optimization of AI systems
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Design and implement security-focused AI agents and reasoning systems
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Develop advanced ML capabilities, including predictive modeling, anomaly detection, and classification
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Adapt and fine-tune LLM technologies for domain-specific security use cases
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Partner with Product, Engineering, and Security teams to deliver measurable business impact
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Provide technical leadership and mentorship across multidisciplinary Data Science initiatives
Requirements:
- M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline
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At least 7 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
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Deep understanding of machine learning theory and practical model behavior
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Strong expertise in Python and the modern Data Science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch / TensorFlow, etc.)
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Solid understanding of LLM architectures and fine-tuning methodologies
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Excellent interpersonal skills and proven ability to work within multidisciplinary product teams
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Strong analytical rigor and structured problem-solving capability
Advantage
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Experience with ML observability, model monitoring, or drift detection.
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Experience with graph technologies, such as Neo4j.
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Experience with Generative AI, RAG, GraphRAG, semantic search, vector databases, or domain-specific LLM fine-tuning / adaptation.
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Experience designing and deploying AI agents or multi-step reasoning systems in on-premise environments.
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Background in network security, firewall policies, or compliance analytics.
