Data Scientist leveraging advanced analytics and machine learning for Gartner’s Client Experience Digital Platform. Leading AI - powered chatbot systems development and collaborative data science projects.
About the role
- Data Scientist leveraging advanced analytics and machine learning for Gartner's Client Experience Digital Platform. Collaborating with cross-functional teams on data science projects while developing AI-powered tools.
Responsibilities
- Work on data science projects in close collaboration with Data Engineering, Application development, Product owners and business leaders to deliver high-value business capabilities
- Build and enhance AI-powered chatbot capabilities to provide intelligent, context-aware client support
- Develop intelligent tools and systems that power conversational AI, including search, recommendation, and content retrieval capabilities
- Build user understanding and personalization models to identify client cohorts and tailor interactions
- Implement and optimize Model Context Protocol (MCP) servers to enable seamless integration between AI agents and enterprise systems
- Leverage internal and external data to understand client's company-level priorities and deliver targeted support
- Maintain high-quality data science solutions with proper documentation and code-reusability principles
- Stay on top of fast-moving AI/ML models and technologies, particularly in the LLM and conversational AI space
- Collaborate with engineering and product teams to launch MVPs and iterate quickly
- Independently plan and drive data science projects that deliver clear business value
Requirements
- 1-3 years hands-on experience building chatbots, conversational AI systems, or other machine learning/artificial intelligence applications to drive business impact
- Bachelor's or Master's Degree in a quantitative field (math, computer science, engineering, etc.) required
- Strong communication skills in technical and business domains with demonstrated ability to translate quantitative analysis into actionable business strategies
- Working experience in some of the following data science areas: Large Language Models (LLMs) and Generative AI, Natural Language Processing and text mining, Conversational AI and chatbot development, Search and Recommendation systems, Prompt engineering and LLM fine-tuning, AI agent architectures and orchestration
- Familiarity with Model Context Protocol (MCP) and building tools for AI agents
- Strong working knowledge of Lean product principles, software development lifecycle, and machine learning life cycle
- Practical, intuitive problem solver with ability to translate business objectives into actionable data science tasks and implement latest ML research
- 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), NoSQL databases (e.g., MongoDB, graph database), vector databases, distributed machine learning (spark), Linux and shell scripting
- Experience with cloud computing services such as AWS 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.
Benefits
- Competitive salary
- Generous paid time off policy
- Charity match program
- Group Medical Insurance
- Parental Leave
- Employee Assistance Program (EAP) and more!
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