Data Scientist, Analytics and Digital Innovation
Hewlett Packard Enterprise
I develop solutions with the Analytics & Digital Innovation Team under the Global Supply Chain Organization. My scope of work includes developing, operationalizing, and/or deploying real-time machine learning, predictive models on very large datasets from across the enterprise (e2e) to enable better business decision-making through real-time data analytics for business users. I am also lead advisor for methodology, research design, model checking and validation within the HPE team.
Areas of research include:
• Machine learning used to predict the expected wait time a sales order line item has from creation to the manufacturing trigger, prior to the availability of all components.
• Econometric modeling and experimentation of neural network architectures for forecasting commodity unit prices.
• Statistical analysis on highly variable behavior contributing to early / late product delivery (cycle time and process analysis)