Lead Data Scientist (Classical ML & Applied AI/LLM/GenAI/Agentic AI)
Core
Lead a hands-on data science team solving ambiguous business problems across supervised/unsupervised learning, causal inference, optimization, and LLM-based agentic AI systems.
Role type
Senior IC Lead Data Scientist (Classical ML & Applied AI/LLM/GenAI/Agentic AI)
Builds
Production RAG/agent workflows, robust observable ML services, and scalable data pipelines.
Domain
Enterprise AI, Applied Machine Learning, Generative AI, Causal Inference
Deliverable
production ML models
Required skills
Linear algebra, probability, optimization, statistical inference, Python (NumPy, pandas, scikit-learn, PyTorch), RAG, agentic workflows, vector databases, deep learning, NLP, causal ML (DML, uplift modeling, IV, propensity scoring), optimization (linear/integer programming, bandits, RL)
Preferred skills
Expert-level Python, cloud computing (AWS/Azure/GCP), experimental design, A/B testing, model governance
Technologies
Langchain, Langgraph, Deepagents, PyTorch, NumPy, pandas, scikit-learn
Responsibilities
Partner with stakeholders to frame ambiguous problems and develop methodologies; Apply LLMs and agentic systems pragmatically and drive adoption; Build and own end-to-end production systems from data cleaning to monitoring; Set technical standards and mentor the team on experimental design and code quality.
Seniority
Senior, hands-on IC with leadership responsibilities
