Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development
Architect AI-powered chatbot systems including intelligent search, recommendation engines, context-aware retrieval, and Model Context Protocol (MCP) servers
Apply transformer-based models, LLMs, and advanced techniques to enhance recommendation relevance
Leverage internal and external data to model client company priorities
Collaborate with engineering, product, UX, and business leaders to prioritize ideas and launch MVPs
Lead a team of data scientists, driving enhancements in accuracy, coverage, latency, scalability, stability, and adoption
Stay current on fast-moving AI/ML advancements

8-12 years of experience in data science, machine learning, or AI
At least 3 years managing data science and engineering teams
Master’s Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required
Proven leadership developing personalization systems, recommendation engines, search/ranking solutions, conversational AI, chatbots, and GenAI applications powered by transformer-based models and LLMs
Strong communication skills to influence executives
Deep expertise in ML lifecycle, Lean product principles, MLOps, experimentation frameworks, and production recommender/GenAI systems
Proficiency with Python, ML frameworks (scikit-learn, NLTK, PyTorch, TensorFlow, Hugging Face, LangChain), SQL/relational databases (Oracle), NoSQL/graph databases (MongoDB), vector databases (Pinecone, Weaviate), distributed ML (Spark), Linux/shell scripting, and cloud platforms (AWS SageMaker, Azure ML).

Director, Data Science

Key skills