Sr Data Scientist

Gartner; Stamford (CT); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive salary

Paid time off

Group Medical Insurance

Parental Leave

Employee Assistance Program

Job summary

Gartner is seeking a Senior Data Scientist to lead complex AI projects and architect advanced agent systems that empower analysts with personalized, scalable experiences.

You will collaborate with IT, PMO, and engineering to deliver high-impact AI capabilities, drive model improvements, and ensure robust production deployments across enterprise platforms.

Qualifications

• 6-8 years of hands-on experience in advanced ML engineering and enterprise tool/product development.
• Bachelor’s degree; Master’s or PhD preferred; strong quantitative background encouraged.
• Strong communication skills to translate ML/AI into actionable business strategy.

Responsibilities

• Lead data science projects with IT, Data Engineering, App development, PMO and business leaders.
• Architect and build agent systems and workflows at scale for Analysts’ experiences.
• Design and implement AI tools for content planning, production and insights creation.

Skills

LLM deployment

Agent systems

Python

NLP engineering

Cross-functional collaboration

Education

Bachelor’s degree

Master’s or PhD preferred

Tools

PyTorch

TensorFlow

HuggingFace

LangChain

LlamaIndex

Pinecone

Weaviate

Spark

Oracle

MongoDB

Job description

About the Role

Join our dynamic BTI Data Science team and help transform Gartner’s research content & insights operation. In partnership with our PMO and IT organizations, you will help build the AI applications and systems that empower our Expert Analysts to perform their work with unprecedented efficiency and depth.

As a Senior Data Scientist, you will lead complex AI and data science projects in partnership with cross‑functional teams and their leaders, steering the development of advanced agent systems and agentic workflows to create intelligent, scalable solutions that deliver tangible value and enhance every step of the Analyst’s journey. You’ll architect and implement cutting‑edge agentic AI solutions while ensuring seamless integration with enterprise platforms.

What You Will Do

• Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high‑value business capabilities
• Architect and build sophisticated agent systems and agentic workflows that provide intelligent, personalized Analyst experiences at scale
• Design and implement advanced AI tools that facilitate human‑in‑the‑loop content planning, content production, and insights creation, prioritizing our Analysts’ expertise
• 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 AI and 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‑re‑usability
• Leverage internal and external data to understand Analysts’ priorities and deliver targeted support
• Collaborate with leadership on long‑term vision, strategy, and solution roadmaps aligned with business objectives
• Pitch ideas, present solutions, and influence senior leaders and stakeholders with strong business value propositions
• Stay on top of fast‑moving AI/ML models and technologies, particularly related to LLMs, multi‑agent systems, agentic workflows, agentic RAG, deep agents, emerging AI architectures, and emerging generative UI/UX solutions
• Collaborate with engineering and product teams to launch MVPs, iterate quickly, and drive solutions toward production
• Independently plan and drive complex data science projects that deliver measurable business value (and measure that value/ROI)
• Mentor junior data scientists in AI Engineering, LLM app development, and best practices

What You Will Need

• 6-8 years of hands‑on experience in advanced ML engineering and enterprise tool/product development, including at least 2 years deploying and managing LLMs in production, and over 1 year designing and implementing agents and multi‑agent systems for enterprise business applications.
• Bachelor’s degree required; Master’s or PhD preferred. While degrees in mathematics, computer science, engineering, or other quantitative fields are advantageous, candidates with a strong academic background in the humanities or other fields who also have relevant experience in quantitative methods, natural language processing (NLP), or artificial intelligence (AI) are encouraged to apply.
• Strong communication skills in technical and business domains with demonstrated ability to translate ML/AI technology solutions into actionable business strategies and influence executive leadership.
• Experience and proficiency with Python, deep learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face), LLM & Agentic frameworks (e.g., LangChain, LangGraph, LlamaIndex), SQL/relational databases (e.g., Oracle), NoSQL databases (e.g., MongoDB, graph database), vector databases (e.g., Pinecone, Weaviate), distributed machine learning (Spark), AI evals and observability solutions.
• Working experience in some of the following AI and data science areas:
  • Large Language Models (LLMs) and Agentic AI
  • Prompt Engineering, Context Engineering, Harness Engineering
  • Conversational AI, chatbot development, and dialogue systems
  • Natural Language Processing and text mining
  • Search and Recommendation systems
  • LLM fine‑tuning, and model optimization
  • AI agent architectures, orchestration, and observability
  • Strong familiarity with Model Context Protocol (MCP) and building tools for AI agents
  • Strong understanding of Lean product principles, software development lifecycle, and ML/AI life cycle
  • Proven ability to translate business objectives into actionable AI and data science tasks and implement state‑of‑the‑art ML/AI research into production systems
  • 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 user and customer‑outcome oriented

What You Will Get

• Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more!
• Collaborative, team‑oriented culture that embraces diversity
• Professional development and unlimited growth opportunities

The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity. Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company’s career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964‑0096 or by sending an email to [e-mail].