Lead Data Scientist in Gurgaon, भारत

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 https://jobeax.com/link/MYJOU8oXAi4eiJi1 digital platformsBuild in-house Agentic products & fine tune LLMs to improve AskGartner and Gartner conferences Agentic productsBuild & optimize Recommender systems for Gartner Global Conferences. These models ensure improved user experience before, during and after a conferenceBuild & Roll-out ML/NLP/Deep learning models to improve Attendees/Exhibitor acquisition & retentionWork closely with business to refine requirements around conferences business, build quick POCs, present findings in a consumable report or streamlit appEnrich conferences client dataset by leveraging scraping, predictive and generative ai tooling & capabilitiesImprove 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 offlineAutomated solutions that help conferences business and strategy teams with analytics and insights capabilities for efficient decision makingWork closely with business and engineering counterparts to develop & deploy solutions involving production grade micro-services, data pipelines, insight dashboardsQualifications:The ideal candidate will have8+ years of hands-on experience in data science alongside a degree in computer science, statistics, mathematics or a related field. Masters or PHD highly preferredHands on experience with GenAI dev tools and frameworks like LangGraph/Langchain, LangfuseExperience building recommender systems, search engine & query pipelines for end user applicationsExperience building and deploying enterprise grade machine learning/NLP/Deep learning, AI Agents in close collaboration with engineering and product managersExperience leveraging and fine-tuning Large Language Models (LLMs) or building/distilling SLMs is a plusSolid programming skills in Python, data science libraries (scikit-learn, TensorFlow/PyTorch, HuggingFace, etc.) and GenAI tools like claude-code, copilotExperience building and deploying machine learning models in close collaboration with engineering - good understanding of CI/CD pipelinesHands-on experience with big data technologies (PySpark) and familiarity with cloud platforms (AWS, GCP, Azure) to explore insights and working with complex datasetsStrong ability to communicate technical concepts to non-technical audiences. (ref:hirist.tech)