Lead a team of technical and non-technical product and program managers responsible for preventing fraudulent purchases on Amazon worldwide through the development of massively scalable distributed systems and the next generation of fraud prevention solutions. The team works closely with one of Amazon's largest machine learning teams as well as talented software engineers to build, deploy, and maintain models to detect and prevent fraudulent activity.Key project areas include multi-year initiatives for anomaly detection including application of temporal graph neural networks, real time optimization of decisions for long-term customer experience, ML systems automation to improve scientist efficiency, model pipeline simplification, challenge (e.g. CVV, TIV, 3DS, etc.) optimization, real-time risk evaluation to achieve ultra-low (<1 bps) fraud rates in target segments, and modeling design changes to support data privacy.

Managed a team of 10+ product managers and business analysts who are responsible for the FBA fulfillment fee revenue we charge on the billions of units shipped each year globally. I have been directly responsibile for the creation and socialization of 80+ pricing recommendation documents for Fulfillment by Amazon businesses in the United States, Canada, Mexico, the United Kingdom, Germany, France, Italy, Spain, Japan, China, India, Australia, and planned new marketplaces. These recommendations range from $20MM to >$100MM in bottom line in-year impact. The recommendations also serve as an annual internal strategic review regarding the growth and profitability of the business across key segments.The team is also responsible for developing tools to ensure the accuracy of charged fees as well as tools and content that assist Amazon FBA sellers with understanding our fee structure. The team handles 25+ fee types for the traditional FBA, FBA Small & Light, FBA Business-to-Business, and FBA Multi-Channel Fulfillment services. The work is global and we interact with leaders across the supply chain. As FBA services emerge, the team plays a key role in establishing launch economics.Served as the interim manager for the FBA Advanced Analytics organization. The team includes product managers, business analysts, machine learning applied scientists, business intelligence engineers, data scientists, and database engineers who collectively are responsible for FBA's data architecture and respond to the most complex data questions for the business.

Manage a team responsible for providing fee structure and magnitude recommendations for the Fulfillment by Amazon business in the United States, Canada, the United Kingdom, Germany, France, Italy, Spain, Japan, China, India, and other planned marketplaces. Expanded the scope of the team to include Revenue Integrity. As part of the scope expansion, led the development of an automated fee audit platform integrated with organizational audit and advisory teams to improve controllership. The platform utilized multiple SQL models to identify potential fee discrepancies, automate alarming and ticketing, and target manual accuracy reviews from global partner teams. The system successfully identified revenue errors as small as 0.0003% of daily fee revenue.

Responsible for providing strategic recommendations for the update of existing fees as well as for creation of new fees to support new marketplaces and services. The position also supports the broader FBA Product Management and Established Markets teams by providing complex financial and operational analysis/modeling as well as strategic recommendations. Analyzed and forecasted the impact to the US, EU, and Japan FBA businesses from changes to the design of product detail pages, the launch of the Add-on Program, and other changes to item level delivery promise logic. Insights provided through these activities supported the creation of the FBA Advanced Analytics team, comprised of econometricians, statisticians, and database engineers.

Managed the internal deployment, business value analysis, and external commercialization of promising health care technologies through a technology incubator platform. Projects involving internal deployment have been integrated with Allscripts PM, McKesson STAR, and PICIS PulseCheck EDIS to improve operational efficiency, patient satisfaction, and revenue capture. Provided financial analysis and marketing support to facilitate a multimillion dollar partnership deal between one of the companies participating in the incubator program and one of the largest health systems in the world.Additional areas of responsibility include service line planning and contract analysis to capitalize on a rapidly shifting market.

Project management for quality improvement efforts as well as the implementation of Allscripts Canopy clinical documentation information system. Allscripts Canopy implementation required coordinating teams from Siemens, McKesson, and Allscripts for a rapid 90-day implementation. Provided system administration support following implementation.