Director of Data, AI

Claroty

. Manage, mentor, and synchronize Data Science, Network Research, and Asset Classification teams .

Posted 9/15/2026full-timeIsraelLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and mentoring cross-functional teams in Data Science and Network Research, with a strong focus on architecting machine learning solutions and integrating complex networking environments. Proven ability to translate industrial protocols into actionable AI features while ensuring accurate asset discovery and risk management.

Highest-signal resume keywords

Network SecurityCybersecurity ResearchMachine Learning LifecycleReverse EngineeringData Science Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep Packet InspectionBlack-Box System AnalysisAI/ML Engineering SolutionsData Collection TechniquesData LineageInformation FusionActionable AI Model FeaturesCPS Architectural ConstraintsOT/ICS Protocols

Soft Skills

MentoringCollaborationCross-Functional SynergyLeadership

Industry Keywords

CIPModbusIoMT ProtocolsDICOM

Tech Stack

Tools & technologies

Cyber Security

About the role

Key responsibilities & impact

Manage, mentor, and synchronize Data Science, Network Research, and Asset Classification teams
Ensure cross-functional synergy and unified product delivery
Architect visibility solutions using domain expertise and advanced machine learning
Scale asset discovery while maintaining accuracy for critical infrastructure
Oversee translation of undocumented industrial and medical protocols into actionable AI model features
Collaborate with data groups, product management, and R&D teams
Translate network visibility into risk management, segmentation, and threat detection policies
Manage passive, active, and integrated data collection techniques
Architect information fusion for individual devices at AI scale across applications, algorithms, and LLMs

Requirements

What you’ll need

7-10+ years of proven experience in network security, cybersecurity research, or data science, with a significant focus on complex networking environments
Demonstrated experience managing R&D, Research, or Data Science groups
Strong engineering foundation with hands-on experience in reverse engineering, deep packet inspection (DPI), or black-box system analysis
Deep understanding of the end-to-end Machine Learning lifecycle and data lineage
Proven ability to leverage AI/ML to scale precise engineering solutions
Familiarity with OT/ICS protocols such as CIP and Modbus, or IoMT protocols such as DICOM
Understanding of CPS architectural constraints
Ability to integrate and collaborate across data science, network engineering, and product management disciplines

Benefits

Comp & perks

Equal-opportunity employer committed to fostering a diverse and inclusive work environment
Special accommodations available upon request in all selection phases