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Applied Scientist II

Microsoft
United States, Washington, Redmond
Jan 01, 2025
OverviewThe Product Ads Algorithm & Infrastructure team in Ads Understanding team is hiring an Applied Scientist II. The team is responsible for product ads selection, relevance, modeling, and online infrastructure for serving and experimenting cutting edge algorithms, ranging from natural language processing (NLP) to information retrieval, computer vision, etc. The team leverages heavily on deep learning methodologies to build solutions to meet the Commerce Strategy of Microsoft, where Product Ads is at the center of it! We are looking for a passionate scientist to deliver an amazing shopping experience with our multi-modal models backing it up.Online Advertising is one of the fastest growing businesses on the Internet today, with about $70 billions 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. Rapid online advertising growth has created enormous opportunities and 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 in this space to grow its share of this market by providing the advertising industry with the state-of-the-art online advertising platform and service. Microsoft Ads Relevance and Revenue (RnR) team is at the core of this effort, responsible for research & development of all the algorithmic components in our advertising technology stack, including:User/query intent (text and image) understanding, document/ad understanding, user targeting - Relevance modeling, IR-based ad retrievalUser response (click & conversion) prediction using large scale machine learning algorithms - Marketplace mechanism design and optimization, and whole-page experience optimization - PersonalizationInnovative new ads productsNetwork protection, fraud detection, traffic quality measurementAdvertising metrics and measurement, including relevance and ad campaign effectivenessData mining and analyticsSupply-demand forecastingAd campaign planning and optimizationExperimentation infrastructure including tools for configuring and launching experiments, dashboard, live marketplace monitoring, and diagnosis.Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
ResponsibilitiesConduct R&D on intelligent search advertising systems 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.Play a key role in driving algorithmic and modeling improvement to the system (esp. using deep learning techniques)Analyze performance and identify opportunities based on offline and online testing. Develop, and deliver robust and scalable solutionsMake direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads.
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