Sr Data Scientist

About the role

Join our dynamic BTI Data Science team and help transform Gartner’s research content & insights operation. In partnership with our PMO and IT organizations, you will help build the AI applications and systems that empower our Expert Analysts to perform their work with unprecedented efficiency and depth.

As a Senior Data Scientist, you will lead complex AI and data science projects in partnership with cross‑functional teams and their leaders, steering the development of advanced agent systems and agentic workflows to create intelligent, scalable solutions that deliver tangible value and enhance every step of the Analyst’s journey. You’ll architect and implement cutting‑edge agentic AI solutions while ensuring seamless integration with enterprise platforms.

• Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high‑value business capabilities.
• Architect and build sophisticated agent systems and agentic workflows that provide intelligent, personalized Analyst experiences at scale.
• Design and implement advanced AI tools that facilitate human‑in‑the‑loop content planning, content production, and insights creation, prioritizing our Analysts’ expertise.
• Design and implement Model Context Protocol (MCP) servers to enable seamless integration between AI agents, enterprise systems, and external tools.
• Build user profiling and personalization models to deliver tailored chatbot experiences.
• Be accountable for high‑quality AI and data science solutions with respect to accuracy, coverage, scalability, stability, and business adoption.
• Take ownership of algorithms and drive enhancements/optimizations based on business requirements with proper documentation and code‑reusability.
• Leverage internal and external data to understand Analysts’ priorities and deliver targeted support.
• Collaborate with leadership on long‑term vision, strategy, and solution roadmaps aligned with business objectives.
• Pitch ideas, present solutions, and influence senior leaders and stakeholders with strong business value propositions.
• Stay on top of fast‑moving AI/ML models and technologies, particularly related to LLMs, multi‑agent systems, agentic workflows, agentic RAG, deep agents, emerging AI architectures, and emerging generative UI/UX solutions.
• Collaborate with engineering and product teams to launch MVPs, iterate quickly, and drive solutions toward production.
• Independently plan and drive complex data science projects that deliver measurable business value (and measure that value/ROI).
• Mentor junior data scientists in AI Engineering, LLM app development, and best practices.

• 6‑8 years of hands‑on experience in advanced ML engineering and enterprise tool/product development, including at least 2 years deploying and managing LLMs in production, and over 1 year designing and implementing agents and multi‑agent systems for enterprise business applications.
• Bachelor’s degree required;
  Master’s or PhD preferred. Degrees in mathematics, computer science, engineering, or other quantitative fields are advantageous, but candidates with a strong academic background in the humanities or other fields who also have relevant experience in quantitative methods, natural language processing (NLP), or artificial intelligence (AI) are encouraged to apply.
• Strong communication skills in technical and business domains with demonstrated ability to translate ML/AI technology solutions into actionable business strategies and influence executive leadership.
• Experience and proficiency with Python, deep learning frameworks (e.g., PyTorch, Tensor Flow, Hugging Face), LLM & Agentic frameworks (e.g., Lang Chain, Lang Graph, Llama Index), SQL/relational databases (e.g., Oracle), No
  
  SQL databases (e.g., MongoDB, graph database), vector databases (e.g., Pinecone, Weaviate), distributed machine learning (Spark), AI evals and observability solutions.
• Working experience in some of the following AI and data science areas:
  Large Language Models (LLMs) and Agentic AI Prompt Engineering, Context Engineering, Harness Engineering;
  Conversational AI, chatbot…