Director, Data Science

As a Director - Data Science at Gartner, Inc., you will play a crucial role in leading high-impact data science initiatives that convert diverse data into actionable insights and decision support. Your responsibilities will include designing, developing, and implementing solutions that drive research excellence, operational efficiency, and revenue growth. This role requires hands-on technical leadership and collaboration with multiple cross-functional stakeholders. **Key Responsibilities:** - Harness advanced technologies to extract, interpret, and visualize insights from large volumes of structured and unstructured data - Collaborate with stakeholders to design, develop, and implement cutting-edge solutions using Machine Learning, Deep Learning, and Generative AI techniques - Innovate in text analytics and develop creative approaches for interpreting complex datasets to deliver impactful recommendations - Own high-visibility programs that translate business objectives into measurable results such as improved engagement, retention, and cost efficiency - Build text analytics and knowledge retrieval capabilities for large-scale unstructured data to generate accurate, explainable insights - Define standards for evaluation, guardrails, prompt engineering, retrieval quality, and hallucination control to ensure trustworthy AI - Enforce best practices in documentation, code reuse, and model lifecycle management while enhancing algorithms to meet evolving needs - Ensure responsible AI practices covering data privacy, IP, safety, and auditability - Mentor and develop a high-performing team of data scientists, fostering a culture of innovation and impact **Qualifications Required:** - Overall experience of 9-11 years in data science/AI/ML roles - Hands-on experience of 6+ years applying ML/DL, NLP, and LLMs to real-world business problems, including text mining and unstructured data analysis - Bachelors or Masters degree in Computer Science, Engineering, Statistics, Mathematics, or related field from a reputed college - Expertise in Agentic AI, RAG pipelines, LLMs, prompt engineering, knowledge graphs, and evaluation frameworks - Proficiency in Python and SQL, with experience in libraries such as Pandas, NumPy, scikit-learn, TensorFlow, PyTorch, SpaCy, NLTK - Practical experience with cloud platforms (Azure/AWS) or GCP for model training, deployment, and scaling - Familiarity with distributed computing (Spark/Databricks) - Strong background in data preparation, cleaning, normalization, and handling large-scale unstructured text data - Knowledge of responsible AI, privacy, auditability, and code management using GitHub/Bitbucket - Basic visualization skills in Excel, Power BI, or Streamlit for dashboards and insights At Gartner, you will enjoy competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP), and more. You will be part of a collaborative, team-oriented culture that embraces diversity and offers professional development and unlimited growth opportunities. Gartner, Inc. is committed to providing equal employment opportunities and offers a hybrid work environment with flexibility and support for personal and professional growth. If you are passionate about making a difference and want to thrive in a purposeful, engaging, and inspiring community, Gartner is the place for you. As a Director - Data Science at Gartner, Inc., you will play a crucial role in leading high-impact data science initiatives that convert diverse data into actionable insights and decision support. Your responsibilities will include designing, developing, and implementing solutions that drive research excellence, operational efficiency, and revenue growth. This role requires hands-on technical leadership and collaboration with multiple cross-functional stakeholders. **Key Responsibilities:** - Harness advanced technologies to extract, interpret, and visualize insights from large volumes of structured and unstructured data - Collaborate with stakeholders to design, develop, and implement cutting-edge solutions using Machine Learning, Deep Learning, and Generative AI techniques - Innovate in text analytics and develop creative approaches for interpreting complex datasets to deliver impactful recommendations - Own high-visibility programs that translate business objectives into measurable results such as improved engagement, retention, and cost efficiency - Build text analytics and knowledge retrieval capabilities for large-scale unstructured data to generate accurate, explainable insights - Define standards for evaluation, guardrails, prompt engineering, retrieval quality, and hallucination control to ensure trustworthy AI - Enforce best practices in documentation, code reuse, and model lifecycle management while enhancing algorithms to meet evolving needs - Ensure responsible AI practices covering data privacy, IP, safety, and auditability - Mento