About the role Join our fast-growing General Product Management Data Science team and help transform Gartner's Client Experience Digital Platform-the essential destination for IT and business leaders worldwide. As a data scientist, you'll leverage advanced analytics and machine learning to create intelligent, scalable solutions that deliver real value and enhance every step of our clients' journey.
In this role, you will lead complex data science projects in partnership with cross-functional teams, driving the development of advanced AI-powered chatbot systems that deliver intelligent, personalized experiences at scale. You'll architect and implement cutting-edge conversational AI tools-including intelligent search, recommendation engines, and context-aware content systems-while ensuring seamless integration with enterprise platforms.
What you will do Lead data science projects in close collaboration with Data Engineering, Application development, Product owners and business leaders to deliver high-value business capabilities
Architect and build sophisticated AI-powered chatbot systems that provide intelligent, personalized client experiences at scale
Design and implement advanced tools that power conversational AI capabilities, including intelligent search, recommendation engines, and context-aware content retrieval systems
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 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 client's company-level priorities and deliver targeted support
Collaborate with senior leadership on long-term vision, strategy, and solution roadmaps aligned with business objectives
Pitch ideas, present solutions, and influence senior leaders and executive stakeholders with strong business value propositions
Stay on top of fast-moving AI/ML models and technologies, particularly in LLMs, conversational AI, and agentic systems
Collaborate with engineering and product teams to launch MVPs and iterate quickly
Independently plan and drive complex data science projects that deliver measurable business value
Mentor junior data scientists on chatbot development, LLM applications, and best practices
What you will need 6-8 years hands‑on experience building conversational AI systems, chatbots, LLM applications, or other advanced machine learning/artificial intelligence solutions to drive business impact
Master's Degree or PhD 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 and influence executive leadership
Working experience in some of the following data science areas:
Large Language Models (LLMs) and Generative AI




Conversational AI, chatbot development, and dialogue systems
Natural Language Processing and text mining
Search and Recommendation systems - nice to have
Prompt engineering, LLM fine-tuning, and model optimization
AI agent architectures and orchestration
Strong familiarity with Model Context Protocol (MCP) and building tools for AI agents
Deep understanding of Lean product principles, software development lifecycle, and machine learning life cycle
Practical, intuitive problem solver with proven ability to translate business objectives into actionable data science tasks and implement state-of-the‑art ML research into production systems
Experience and proficiency with Python, machine learning tools (e.G., scikit‑learn, spacy, nltk), deep learning frameworks (e.G., pytorch, tensorflow, huggingface), LLM frameworks (e.G., LangChain, LlamaIndex), SQL/relational databases (e.G., Oracle), NoSQL databases (e.G., MongoDB, graph database, vector databases, {…} etc)
Experience with cloud computing services such as AWS or Azure ML
Strong ability to work collaboratively across product, data science and technical stakeholders with experience mentoring data scientists
Ability to work in a culture that thrives on feedback and seeks opportunities to stretch outside comfort zone
Bias for action and client outcome oriented
What you will get: Competitive compensation
25 days annual holiday and an additional day off for your birthday.
Private Medical and Dental Care.
Life and Disability Insurance.
Public Transport Subsidy.
Ticket Restaurant Card.
Childcare Vouchers (Ticket Guarderia).
IncentiFit - annual reimbursement for health-and-wellness-r
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