Ritish Chugh is an analytics and data science leader with over a decade of experience designing and scaling data, AI, and decision-support systems in complex, regulated, and high-impact environments. His work focuses on operational analytics, semantic metric layers, data governance, and AI-enabled decision systems—particularly where data quality, trust, and automation directly influence executive decisions and regulatory outcomes. He has led and advised initiatives spanning finance, risk, compliance, and global operations, translating large-scale data into systems that are relied upon by senior leadership and cross-functional stakeholders.

Ritish is an active contributor to the professional analytics community through speaking engagements, peer review, and published practitioner and industry articles. He regularly collaborates with researchers and practitioners to bridge theory and real-world implementation, with a particular interest in conversational analytics, metric integrity, and AI adoption at scale. He is a Senior Member of IEEE and an active member of INFORMS and other professional societies, and he enjoys contributing to forums that emphasize rigor, practical impact, and responsible AI deployment.