Data Science Team Leader
2 days ago
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:
- 5+ years of experience in data science or machine learning, including 2+ years in a leadership or mentoring role.
- 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.
- Experience with LLMs, RAG architectures, or graph-based modeling (Neo4j, NetworkX).
- Familiarity with on-prem and hybrid AI deployment architectures.
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