Neil Caraos

Established the Data Science Quantitative Insights team, focusing on applying statistical analysis to provide key data-driven insights for business decision-making and performance optimization. Analyzed performance data for 100+ Amazon clients representing $200M+ in annual revenue, delivering actionable insights and strategic recommendations to optimize dynamic pricing models and PPC campaigns, re

Supported the Industry 4.0 Digital Transformation project by developing an automated data pipeline workflow, including establishing data collection pipelines from equipment sensors and characterization/metrology instruments, performing extract-transform-load (ETL) on raw data to create data warehouses using AWS, PostgreSQL, NodeRED, and Python, and creating data visualization dashboards and analyt

Created process monitoring dashboards using PI ProcessBook software, consisting of pertinent equipment parameters and process variables, to enable data-driven insights and proactive engineering actions for detecting potential issues and identifying improvement opportunities. Co-led a core team of 6 engineers in a complex engineering change involving a refinery power source alternative, successfull

Currently pursuing a Postgraduate Diploma in Artificial Intelligence and Machine Learning to deepen expertise in machine learning applications, reinforcement learning, LLMs and generative AI. Relevant coursework included Machine Learning, Reinforced Learning, Generative AI, and LLMs.

Completed a Master of Science in Innovation and Business. Relevant coursework included Managerial Economics, Corporate Finance, Innovation Strategy, Accounting, Managing Human Capital, Technopreneurship, AI, and Data Visualization.

Grade: Magna Cum Laude

Graduated Magna Cum Laude with a Bachelor of Science in Chemical Engineering. Relevant coursework included Chemical Engineering Calculations, Environmental Engineering, Engineering Economics, Thermodynamics, and Statistics.