Description
The Ads Monetization Algo team at Microsoft Advertising focuses on optimizing ad performance for all advertisers in our ecosystem by bidding on their behalf in real-time auctions across our marketplaces. We are also responsible for designing and optimizing the auctions for the long term. All of these works are done through algorithm development, optimization, and experimental analysis of advertiser strategies and auction mechanisms.
In our team, applied scientists work together and utilize all sorts of platforms, techniques, and approaches, including but not limited to mathematical modeling and optimization, machine learning, optimal control, game theory, and general economics and operations research. We build and develop both online stacks as well as offline workflows to support our algorithms. At its core, our team utilizes signals of user and advertiser intent as well as auction characteristics to determine in real-time or near-real-time which ads can enter the auctions. Our work directly impacts 10+ billion dollars in revenue annually.
We are looking for a highly skilled applied scientist with development and management skills and a background in quantitative fields such as statistical machine learning, decision theory, operations research, optimization theory, mathematical modeling, data mining, causal inference, information retrieval, game theory, mechanism design, and optimal control. They will play a key role in driving algorithmic improvements to online and offline systems, developing and delivering robust and scalable solutions, making direct impacts on advertisers’ experience and the ad marketplace’s long-term health to collectively and continually increase the revenue for Microsoft Advertising.