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 the intelligence behind 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.
Responsibilities:
• 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
• Develop advanced ML capabilities, including predictive modeling, anomaly detection, classification, and behavioral analysis
• Develop the intelligent capabilities behind security AI agents, combining machine learning, LLMs, statistical methods, and domain-specific algorithms, with a strong understanding of how agents use these capabilities within multi-step workflows
• Adapt and fine-tune LLM technologies for domain-specific security use cases
• Define and implement rigorous evaluation methodologies for ML and agentic AI systems, including decision quality, reliability, robustness, uncertainty, and failure modes
• Partner with Product, Engineering, and Security teams to deliver measurable business impact
• 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
• At least 7 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
• Deep understanding of machine learning theory, statistical reasoning, and practical model behavior
• Strong expertise in Python and the modern Data Science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch / TensorFlow, etc.)
• Strong understanding of LLM architectures, adaptation and fine-tuning methodologies
• Strong understanding of AI agent architectures and concepts, including tool use, context management, memory, planning/reasoning, and multi-step workflows
• Strong analytical rigor and structured problem-solving capability
• Excellent interpersonal skills and proven ability to work within multidisciplinary product teams
Advantage:
• Experience developing or deploying AI agents or multi-step reasoning systems
• Experience with local/on-premise AI systems, particularly under constrained compute, memory, latency, or security requirements
• Experience with small language models (SLMs), model quantization, distillation, efficient inference, or other techniques for running AI models locally
• Experience with Generative AI, RAG, GraphRAG, semantic search, vector databases, or domain-specific LLM adaptation
• Experience with ML/AI observability, model monitoring, or drift detection
• Experience with graph technologies, such as Neo4j
• Background in network security, firewall policies, or compliance analytics
Skills Required
- M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline
- At least 7 years of hands-on Data Science experience delivering end-to-end solutions into production environments
- Deep understanding of machine learning theory, statistical reasoning, and practical model behavior
- Strong expertise in Python and the modern Data Science ecosystem, including NumPy, Pandas, Scikit-learn, PyTorch, or TensorFlow
- Strong understanding of LLM architectures, adaptation, and fine-tuning methodologies
- Strong understanding of AI agent architectures, including tool use, context management, memory, planning, reasoning, and multi-step workflows
- Strong analytical rigor and structured problem-solving capability
- Excellent interpersonal skills and ability to work within multidisciplinary product teams
- Experience developing or deploying AI agents or multi-step reasoning systems
- Experience with local or on-premise AI systems under constrained compute, memory, latency, or security requirements
- Experience with small language models, model quantization, distillation, efficient inference, or other local AI techniques
- Experience with Generative AI, RAG, GraphRAG, semantic search, vector databases, or domain-specific LLM adaptation
- Experience with ML/AI observability, model monitoring, or drift detection
- Experience with graph technologies such as Neo4j
- Background in network security, firewall policies, or compliance analytics
What the Team is Saying
Tufin Compensation & Benefits Highlights
-
Healthcare Strength — Medical, dental, and vision coverage are paired with mental‑health support, life and disability insurance, and EAP access. Wellness options such as yoga, meditation, and gym or sport activities are also promoted.
-
Leave & Time Off Breadth — Flexible or unlimited PTO sits alongside paid holidays, sick time, bereavement leave, and paid volunteer time. This breadth of time‑off options is positioned to support work–life balance.
-
Parental & Family Support — Paid parental leave is explicitly offered, and some offices provide an onsite Mother’s Room. Family medical leave is also highlighted for caregiving needs.
Tufin Insights
What We Do
Tufin is a world leading network security policy management company, managing and automating security changes across next gen firewalls and network devices. We are a hybrid technology, supporting on/off prem and cloud services. The automation orchestration piece is what sets us apart in the market, as this allows us to help our customers to implement their security changes in hours or minutes vs. days. Since going public in April 2019, Tufin has continued to be the market leader in the space!
Why Work With Us
Here at Tufin, we pride ourselves on being a transparent organization where the door is always open & treating others with respect and care is our top value (hence our “no asshole” policy). We believe that every employee is important in achieving our mission & as we continue to grow, we are making sure that we are maintaining our unique culture.
Gallery
Tufin Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
