I lead AWS Bill Computation, which is responsible for ensuring that every AWS customer gets timely, accurate bills reflecting their usage and pricing terms. Our work covers every service in AWS worldwide and every AWS customer. Our highest priority is earning customer trust, which we do by making bills as simple, reliable, and transparent as possible. To do that, we process petabytes of data about every job run on every AWS service and build systems that manage the expansive variety of contracts, services, and customer needs.

Led the organization responsible for the foundations for commerce at Facebook. My team focused on ensuring that each of our 1B+ monthly active users could find relevant products on Marketplace. We personalized their Marketplace Feed based on their interests, delivered relevant Search results, and targeted Notifications and News Feed placements to bring Facebook App users to Marketplace at the right time to serve their needs. We used best-in-class machine learning methods and work to understand both customers and listings on Marketplace, including creating all Structured Data, Taxonomy, and Listing Quality information.

Led the organizations responsible for Integrity (safety, trust, policy enforcement) and Product Intelligence (structured data, product taxonomy, listing quality) for Facebook Marketplace and Facebook Jobs.

At Amazon, I was the single-threaded leader for Retail Pricing. My organization was responsible for setting prices for every retail item sold by Amazon, and ensuring those prices are timely and accurate as the competitive landscape of prices evolves. My organization of hundreds of software developers, applied scientists, research scientists, product managers, and program managers was world-class in its use of machine learning and distributed, event-based systems to handle the breadth and scale of Amazon's pricing needs.

Improved revenue by more than $500MM by transforming eBay's systems while leading a team of 170 engineers and researchers across two organizations. Traffic Engineering was responsible for eBay's external traffic drivers, including Paid Search Advertising, Display Advertising, the eBay Partner Network, E-mail, Data Feeds, and OEM Marketing. Trust Science was an applied science team responsible for reducing fraud on eBay and improving customer trust.

Grew a team of engineers and scientists from 40 to 120 to improve the quality of eBay's Search results. Responsible for science advances at the heart of Cassini, eBay's next-generation search engine, and for driving $250MM in revenue by helping customers find items to purchase faster through better search.

Led a team of of 35+ researchers, research engineers, and analysts. Areas of responsibility include relevance, monetization, user behavior analysis, and a number of product features such as vertical category suggestion, spelling correction, and news. For 5 consecutive quarters, Searchme reigned as the fastest-improving web search engine based on measurement of web relevance (DCG5).

Led a team team of 25 researchers and engineers using machine learning to improve Yahoo!'s web search ranking at a time when Yahoo! was competing fiercely with Google for market share through better relevance and features.

Core member of the team at AltaVista developing the world's first machine-learned search ranking system. Developed ground-breaking systems for automatic spam detection and spelling correction which were turned into key products at Yahoo!, Inc. after Overture was acquired.