Data Scientist

Role Overview: As a Data Scientist at our company, you will lead high impact Data Science initiatives that convert diverse data into actionable insights and decision support. Your responsibilities will include designing, executing, and implementing solutions that drive research excellence, operational efficiency, and revenue growth. Key Responsibilities: - Partner with stakeholders to frame the problem and work directly with technical leaders and domain experts to translate ambiguous questions into well-posed analytical problems - Develop methodologies across the full spectrum, applying and extending methods across supervised learning, unsupervised learning, Generative / Agentic AI, NLP, etc. - Deliver production-ready solutions by deriving approaches from first principles, prototyping hands-on, and carrying solutions from data cleaning and feature engineering through model development, evaluation, deployment - Communicate insights in business terms by conveying complex technical concepts to diverse audiences and influencing key stakeholders and leaders across the organization Qualifications Required: - 3-6 years in applied ML / applied AI, with hands-on experience building and deploying models in production environments - Bachelor's or Master's (or PhD) in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field - Demonstrated experience working across multiple areas such as supervised ML, unsupervised ML, optimization, recommendation systems, forecasting, and LLM/agentic systems/ RAG, agentic workflows, evaluation frameworks, prompt engineering, fine-tuning trade-offs, and vector databases - Experience with graph algorithms is a plus, as well as business applications such as churn analysis, customer profiling, and recommendation systems - Strong expertise in Python, distributed computing (Spark / Snowflake / BigQuery), and Cloud platforms (AWS / Azure / GCP) - Knowledge of Agentic AI Frameworks like LangChain, LangGraph, and Deep-Agents or equivalent, as well as deep learning fundamentals Company Details: At Gartner, Inc., we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission-critical priorities. Since our founding in 1979, weve grown to 20,000 associates globally who support over 13,000 client enterprises in ~90 countries and territories. We offer a collaborative, team-oriented culture that embraces diversity and provides professional development and unlimited growth opportunities. Role Overview: As a Data Scientist at our company, you will lead high impact Data Science initiatives that convert diverse data into actionable insights and decision support. Your responsibilities will include designing, executing, and implementing solutions that drive research excellence, operational efficiency, and revenue growth. Key Responsibilities: - Partner with stakeholders to frame the problem and work directly with technical leaders and domain experts to translate ambiguous questions into well-posed analytical problems - Develop methodologies across the full spectrum, applying and extending methods across supervised learning, unsupervised learning, Generative / Agentic AI, NLP, etc. - Deliver production-ready solutions by deriving approaches from first principles, prototyping hands-on, and carrying solutions from data cleaning and feature engineering through model development, evaluation, deployment - Communicate insights in business terms by conveying complex technical concepts to diverse audiences and influencing key stakeholders and leaders across the organization Qualifications Required: - 3-6 years in applied ML / applied AI, with hands-on experience building and deploying models in production environments - Bachelor's or Master's (or PhD) in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field - Demonstrated experience working across multiple areas such as supervised ML, unsupervised ML, optimization, recommendation systems, forecasting, and LLM/agentic systems/ RAG, agentic workflows, evaluation frameworks, prompt engineering, fine-tuning trade-offs, and vector databases - Experience with graph algorithms is a plus, as well as business applications such as churn analysis, customer profiling, and recommendation systems - Strong expertise in Python, distributed computing (Spark / Snowflake / BigQuery), and Cloud platforms (AWS / Azure / GCP) - Knowledge of Agentic AI Frameworks like LangChain, LangGraph, and Deep-Agents or equivalent, as well as deep learning fundamentals Company Details: At Gartner, Inc., we guide the leaders who shape the world. Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission-critical p