Online Advertising is one of the fastest growing businesses on the Internet today, with about $70 billion of a $600 billion advertising market already online. Search engines, web publishers, major ad networks, and ad exchanges are now serving billions of ad impressions per day and generating terabytes of user events data every day. The rapid growth of online advertising has created enormous opportunities as well as technical challenges that demand computational intelligence. Computational Advertising has emerged as a new interdisciplinary field that involves information retrieval, machine learning, data mining, statistics, operations research, and micro-economics, to solve challenging problems that arise in online advertising. The central problem of computational advertising is to select an optimized slate of eligible ads for a user to maximize a total utility function that captures the expected revenue, user experience and return on investment for advertisers. Microsoft is innovating rapidly
We are looking for an Applied Scientist with R and D background to conduct research and development on intelligent search advertising system to mine and learn actionable insights from large scale data and signals we collect from user queries and online activities, advertiser created campaigns and their performances, and myriad responses from the parties touched by the system in Bing ads paid search ecosystem. The person will play a key role to drive algorithmic and modeling improvement to the system, analyze performance and identify opportunities based on offline and online testing, develop and
Outstanding expertise and research experience on statistical machine learning, data mining, information retrieval, statistical natural language processing, deep learning, and/or computer vision. Excellent problem solving and data analysis skills. Passionate, self-motivated. Effective communication skills, both verbal and written. Strong software design and development skills/experience. Experience Required: MS degree in CS/EE or related areas is required. PhD degree is preferred. Familiarity with distributed data processing/analysis and modeling paradigm, such as Map-Reduce and MPI, is preferred