Data Scientist, Digital Enablement & Innovation
Hewlett Packard Enterprise
I develop solutions with the Digital Enablement & Innovation team under HPE Global Operations. My scope of work includes developing, operationalizing, and/or deploying machine learning, predictive models on very large datasets from across the enterprise (e2e) to enable better business decision-making 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 has from creation to the manufacturing trigger, prior to the availability of all components.
• Machine learning used to predict individual sales order milestones, from the time a customer initiates a sales order, manufacturing begins and ends, and the sales order is sent to the hub within inbound logistics.
• Operationalizing econometric models and designing neural network architectures for forecasting high-value commodities within supply chain procurement.
• Statistical analysis to identify highly variable behavior contributing to early / late product delivery within order and supply chain analytics.