• Developed the first machine learning model in the operations group, connecting to 12 different internal and external databases, and leveraging an XGBoost algorithm to give accurate weekly predictions for individual customers and individual processors to influence supply and demand planning• Leveraged transfer learning from pre-trained models to expedite development timelines and enhance model performance.• Utilized large language models to generate comprehensive and contextually accurate image captions, enhancing image understanding and accessibility.• Conceived and initiated a cross-corporation machine learning group to propagate machine and deep learning techniques across other divisions in the organization, including to PCs, IoT, and Datacenter• Recruited and mentored new data scientists in order to build organizational competency around machine learning and advanced analytic techniques • Developed a comprehensive processor and device market models covering a wide range of products across servers, workstations, storage, and networking which provided framework for many significant business decisions over several years• Developed a softmax & a classification model from daily telemetry data to identify processor marketing and pricing gaps that drove pricing actions and changes in marketing strategy across business units

• Developed a tool to optimize costs/availability tradeoffs from maintenance (scheduled and unscheduled) on a major defense program, modeling the cost implications on spares, budgets, and availability• Consulted major organizations on logistical challenges and solved them with advanced analytics and machine learning models, driving millions of dollars in cost savings • Developed a dynamic web-based optimization tool with an RShiny front-end to assess total cost of ownership of a major piece of infrastructure and identified ways to optimize on both cost and operational metrics, generating significant program savings• Developed mixed integer programming optimization models to evaluate tradeoffs between cost and asset uptime by determining the optimal portfolio of spares

• Provided internal technical leadership on developing IT market forecasting models on key projects for Fortune 500 clients• Responsible for client and project management on a new account, and successfully built a long-term client relationship • Developed and successfully marketed a dynamic, Excel-based simulation model and assisted a new client in alternative scenario planning • Developed a proprietary hedonic price model for a Fortune 500 company looking to evaluate brand premium to inform major corporate decisions• Developed Bass Diffusion Models in SAS based on market data for a multi-national corporation to study tablet and smartphone adoption across 70 countries

• Introduced the use of R in conjunction with SAS in order to maximize efficiency; developing a new strategy for econometric models using leading economic indicators to forecast IT markets for G-7 and BRIC countries• Performed competitive intelligence analysis on leading IT companies by analyzing and integrating quarterly reports, third party sources, and propriety modeling• Developed a dynamic global sales predictive model for a Fortune 500 client based on market and economic indicators to inform regional investment and inventory decisions • Created comprehensive dashboards summarizing key IT market trends for key executives of a Fortune 500 client