Rishi Pandey

Data-driven professional with over 5 years of experience in data science, big data engineering, and research focused analytics across academic and industrial settings. Proven expertise in process monitoring, machine learning, and statistical modelling with a strong foundation in data architecture and analytical tools. Currently serving as a Postdoctoral Researcher at the Technological University of the Shannon, delivering industry focused AI and data analytics solutions while leading cross-functional collaborations and teaching engagements. Experience working with pharmaceutical industry partners in alignment with cGMP principles, ensuring data integrity and validation support for regulated environments.

Built a predictive model that increased production efficiency for ELI Lilly. • Optimized ETL processes that enhanced data quality and consistency. AI-Driven Production Stage Sensing for Smart Predictive Maintenance Analytics (Forthcoming 2024) Co-authored a paper currently under review, focusing on stage-wise process classification using deep learning models for predictive maintenance in smart manufacturing environments. • Banking Data Migration: Successfully migrated data pipelines for a top financial institution, significantly improving data retrieval speed and reducing storage redundancy. • ETL Optimization: Enhanced data quality and consistency by streamlining ETL pipelines, leading to improved analytics reliability across operational dashboards.