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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 hasas 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.online advertising platform and service. Ads Relevance and Revenue () team is at the core of this effort, responsible for research & development of all the algorithmic components in our advertising technology stack, including,
Large scale machine learning algorithms and platform
We heavily use the recent advances in grid or cloud computing infrastructure to harness hugeof data for solving many of the above-mentioned problems. We love big data! Theour business. Our experimentation infrastructure allows us to innovate and test new algorithms rapidly with live traffic to measure theireffectiveness, andlaunch them in production as soon as they produce positive results, which makes our work environment productive and rewarding.
Preferred Qualifications:
cientist with deep R&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 inads paid search ecosystem. The person will play a key role to drive algorithmic and modeling improvement to the system, analyze performance andopportunities based on offline and online testing,and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue.
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