Director, Data Science

Gartner•Stamford, CT

8h•$122,000 - $168,000

About The Position

About the Role This is a senior leadership role on the Global Product Management Data Science team managing the Client Experience Digital Platform — the central hub where clients interact with Gartner to unlock value. Our clients are IT and business leaders worldwide, relying on the platform embedded in their workflows for critical priorities. Our mission is to accelerate innovation through intelligent digital products that disrupt the market and ourselves — constantly seeking data science leaders to champion this vision. The Director, Data Science will lead efforts across personalization, recommendation systems, and GenAI chatbot tools, delivering scalable intelligence that drives hyper-personalized experiences and business outcomes.

Requirements

8-12 years of experience in data science, machine learning, or AI, with 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.
Demonstrated success translating business priorities into technical roadmaps, driving cross-functional execution, and delivering production ML systems with clear business impact.
Strong communication skills to influence executives, translating complex analysis into compelling strategies and value propositions.
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).
Working experience in: Large Language Models/Generative AI, conversational AI/chatbot development, NLP/text mining, search & recommendation systems, prompt engineering/LLM optimization, AI agent architectures.
Collaborative leader who thrives in feedback-driven cultures with bias for action and client outcomes.

Responsibilities

Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development, owning strategy for user profiling, content matching, ranking, conversational AI, and next-best-action systems.
Architect AI-powered chatbot systems including intelligent search, recommendation engines, context-aware retrieval, and Model Context Protocol (MCP) servers for seamless AI agent integration with enterprise systems and external tools.
Apply transformer-based models, LLMs, and advanced techniques to enhance recommendation relevance, search optimization, user personalization, and scalable GenAI solutions.
Leverage internal and external data to model client company priorities, competitive landscapes, engagement signals, and deliver targeted support.
Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value.
Lead a team of data scientists, driving enhancements in accuracy, coverage, latency, scalability, stability, and adoption while maintaining strong MLOps practices.
Translate quantitative analysis into actionable strategies, pitch high-impact ideas, and influence senior leadership on long-term vision and solution roadmaps.
Stay current on fast-moving AI/ML advancements, particularly LLMs, conversational AI, agentic systems, and transformer architectures.