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• Organized and validated large datasets to identify patterns in hiring rates, skill demands, and workforce dynamics• Analyzed hiring trends within the CDMO, CRO, Pharma, and CGT sectors using Python, Power BI, SQL, and Excel, increasing data-driven decision-making accuracy by 20%• Developed a comprehensive 'Talent Index' using Data Envelopment Analysis (DEA) to evaluate talent availability, skill levels, and industry trends• Organized huge data sets effectively via advanced querying, visualization, and analytics tools Designed and implemented machine learning models for Predictive Talent Market Dynamics, achieving a 95% accuracy rate in predicting biomanufacturing talent supply and demand• Processed structured/unstructured data & gained insights by leveraging predictive modelling, statistics, ML & data mining• Conducted financial trend analysis of 150+ companies using UiPath, Phantom Buster, and Octoparse for data scraping and automation, providing strategic insights from key financial metrics.• Presented findings and reports to contribute insights to Biopharma 4.0 and Digital Biomanufacturing talent research articles