About the role :

This is a unique opportunity to join our fast-growing Global Product Management Data Science team. You will be working with the team managing The Client Experience Digital Platform which is the go-to place for all clients to interact with Gartner to get value. Our clients are IT and business leaders around the world. They expect to get help from Gartner on their most critical priorities.

The Digital Platform is embedded in their workflows to help them on every step of their journey. Our mission is to deliver tremendous client value by building scalable, intelligent digital products and solutions. We are constantly looking for product management, UX and data science leaders to help us accelerate innovation to disrupt the marketplace and disrupt ourselves.

What you will do :

- Work on Data science projects in close collaboration with the Data Engineering team, Application development team, Product owners and business leaders to deliver high value business capabilities

- Develop and enhance Gartners client-facing products by leveraging state-of-the-art technologies and frameworks to deliver accurate and contextually relevant responses to user queries across search and chat platforms.

- Develop intelligent tools and systems that power conversational AI, including search, recommendation, and content retrieval capabilities.

- Integrate diverse data sources and services into existing Gartner platforms utilizing tool-based agentic architectures, driving increased platform value, scalability, and innovation.

- Build user query understanding and intent refinement models to refine query to content similarity

- Be responsible for high quality data science solutions with respect to accuracy and coverage.

- Be accountable for solutions scalability, stability, and business adoption

- Responsible for maintaining proper documentation and further code-reusability principles

- Responsible for ownership of algorithms and its enhancements/optimizations as per business requirement

- Collaborate with Director, Data Science in long term vision, strategy, and solution roadmap to align with bigger business objectives and mission critical priorities of the organization

- Responsible to pitch ideas, present solutions and influence senior leaders with strong business value propositions

- Stay on top of fast-moving AI/ML models and technologies. Understand and follow disruptive data science solutions

- Collaborate with engineering and product teams to launch MVPs and iterate quickly

- Independently plan and drive data science projects that deliver clear business value

What you will need :

- 6 to 8 years of hands-on experience designing and developing agentic AI applications utilizing MCP servers, advanced search systems, or other machine learning/artificial intelligence solutions to deliver measurable business impact.

- Bachelors degree required while a masters degree in a quantitative field (math, computer science, engineering, etc.) is strongly preferred

- Demonstrated ability to translate quantitative analysis into actionable business strategies with strong communication skills in technical and business domains.

- Demonstrated expertise in assessing model outputs and converting insights into actionable strategies that drive measurable business impact, with a focus on ensuring that analytical solutions deliver tangible and quantifiable value beyond model development.

- Working experience in some of the following data science areas :

a. LLMs, Generative AI, and RAG based Applications

b. AI agent architectures and orchestration

c. Conversational AI and chatbot development

d. Text mining and Natural Language Processing

e. Search or Recommendation systems

f. Data analytics with multi-dimensional data

- Familiarity with Model Context Protocol (MCP) and building tools for AI agents to enable seamless integration between AI agents and enterprise systems

- Strong working knowledge of Lean product principles, software development lifecycle, and machine learning life cycle

- Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies

- Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning frameworks (e.g., huggingface, pytorch, tensorflow), LLM frameworks (e.g., LangChain, LlamaIndex), SQL/relational databases (e.g., Oracle), Graph database, vector databases, distributed machine learning (spark), Linux and shell scripting

- Experience with cloud computing services such as AWS, GCP or Azure ML

- Ability to work collaboratively across product, data science and technical stakeholders in a culture that thrives on feedback

- Bias for action and client outcome oriented