Data Science Team Leader

We’re looking for a hands-on Data Science Team Leader to lead a team of talented data scientists in developing cutting-edge AI and machine learning solutions that power our next-generation security and automation products. You’ll combine technical depth, leadership, and creativity to translate complex data into intelligent, impactful features across our product ecosystem.

Key Responsibilities

• Lead and mentor a team of data scientists in designing, training, and deploying ML/AI models for production.
• Define the team’s roadmap and priorities in alignment with product and engineering leadership.
• Work closely with AI Engineering and the Product team to transform research ideas into scalable solutions.
• Oversee the full model lifecycle: data collection, feature engineering, experimentation, evaluation, and deployment.
• Drive innovation through applied research in NLP, LLMs, graph analytics, anomaly detection, and predictive modeling.
• Translate ambiguous or domain-specific problems into rigorous ML / deep learning research initiatives.
• Ensure best practices for reproducible ML pipelines, code quality, documentation, and experimentation tracking (e.g., MLflow/W&B).
• Standardize modeling approaches and libraries across your data science team to maintain consistency and reuse.
• Work with large, heterogeneous datasets and apply statistical / ML techniques to derive meaningful insights and predictions.
• Stay ahead of trends in AI and data science and identify opportunities to integrate emerging technologies into the product.

Why Join Us?

• Lead a strategic data science team building AI-powered core features for an industry-leading security platform.
• Work in a culture that values innovation, ownership, and scientific excellence.
• Collaborate with a world-class R&D organization shaping the future of AI-driven network security.

Requirements:

• 2+ years in a leadership or managing a team
• 5+ years of experience in data science or machine learning
• Strong background in Python, ML frameworks (TensorFlow, PyTorch, scikit-learn), and data processing tools (Pandas, Spark, SQL).
• Proven experience in algorithms development, optimization, or custom modeling beyond out-of-the-box solutions.
• Proven ability to lead research-to-production projects in collaboration with software engineers.
• Solid understanding of statistics, probability, and experimental design.
• Excellent communication skills and ability to translate complex ideas into actionable plans.
• BSc/MSc/PhD in Computer Science, Mathematics, Statistics, or related field.

Advantage

• Background in network security - Big advantage.
• Experience with LLMs, RAG architectures, or graph-based modeling (Neo4j, NetworkX).
• Familiarity with on-prem and hybrid AI deployment architectures.