As a Lead Data Scientist, you will:

- Build and enhance AskGartner (Gartners AI Advisor) with insights and capabilities from Gartner events and ensure seamless user experience between Events and Gartner.com digital platforms
- Build in-house Agentic products & fine tune LLMs to improve AskGartner and Gartner conferences Agentic products
- Build & optimize Recommender systems for Gartner Global Conferences. These models ensure improved user experience before, during and after a conference
- Build & Roll-out ML/NLP/Deep learning models to improve Attendees/Exhibitor acquisition & retention
- Work closely with business to refine requirements around conferences business, build quick POCs, present findings in a consumable report or streamlit app
- Enrich conferences client dataset by leveraging scraping, predictive and generative ai tooling & capabilities
- Improve upon MLOps capabilities by building and optimizing data pipelines, model monitoring and training capabilities
- Build Evaluation Frameworks to ensure products development are tied to metrics that move the needle and can be measured offline
- Automated solutions that help conferences business and strategy teams with analytics and insights capabilities for efficient decision making
- Work closely with business and engineering counterparts to develop & deploy solutions involving production grade micro-services,



data pipelines, insight dashboards

Qualifications

The ideal candidate will have

- 8 years of hands-on experience in data science alongside a degree in computer science, statistics, mathematics or a related field. Masters or PHD highly preferred
- Hands on experience with GenAI dev tools and frameworks like LangGraph/Langchain, Langfuse
- Experience building recommender systems, search engine & query pipelines for end user applications
- Experience building and deploying enterprise grade machine learning/NLP/Deep learning, AI Agents in close collaboration with engineering and product managers
- Experience leveraging and fine-tuning Large Language Models (LLMs) or building/distilling SLMs is a plus
- Solid programming skills in Python, data science libraries (scikit-learn, TensorFlow/PyTorch, HuggingFace, etc.) and GenAI tools like claude-code, copilot
- Experience building and deploying machine learning models in close collaboration with engineering - valuable understanding of CI/CD pipelines
- Hands-on experience with big data technologies (PySpark) and familiarity with cloud platforms (AWS, GCP, Azure) to explore insights and working with complex datasets
- Strong ability to communicate technical concepts to non-technical audiences.

📌 Lead Data Scientist (India)
🏢 Gartner
📍 India