Amit Kulkarni

Architected a 0-to-1 global Customer Data Platform (CDP) that unified 9M+ guest profiles using deterministic and probabilistic identity resolution. Established data governance and quality SLAs, improving data retrieval accuracy by 93% and reducing search latency from 5 minutes to 20 seconds.

Led the 0-to-1 design and launch of LodgIQ RM, an AI-powered RMS using outside-in forecasting and dynamic ML, delivering a 15% increase in RevPAR index. Rolled out SAS/ML optimization engines across global portfolios, including GroupIQ and ForecastIQ, driving a 26% increase in total revenue and ~22% average RevPAR uplift.

Bridged revenue science and product strategy to translate forecasting and optimization capabilities into scalable product features, improving RevPAR index by 15% and increasing user engagement by 25% within six months. Designed and implemented a global CDP covering 9M+ guest profiles and introduced backlog governance and stakeholder alignment to strengthen delivery across teams.

Managed end-to-end validation and certification of high-power SAS analytics models for forecasting and decision optimization, supporting 10B+ automated commercial decisions daily. Collaborated with data scientists to assess unconstrained demand and contributed to G3 RMS features that achieved an average 22% increase in RevPAR.

Interpreted hotel forecasts and translated them into pricing and inventory decisions, improving commercial decision-making with portfolio performance insights. Built client relationships by positioning analytics as decision support rather than reporting.

Completed a Bachelor's degree in Hotel Management and Catering Technology at AISSMS College of HMCT in Pune, India.