New 
Principal Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Nov 29, 2024 | |
|
OverviewWe are looking for aPrincipal Applied Scientist in Redmond, WA or Mountain View, CA to incubate technologies from end to end to make product impact to drive innovations in the stack. 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 both users and advertisers experience, and continually increasing the revenue for Microsoft Ads. They will heavily use the recent advances in grid or cloud computing infrastructure to harness huge volume of data for solving many of the above-mentioned problems and leverage large language models (LLM) for many of the problems. The Microsoft Advertising Marketplace team is a world-class Research and Development team of talented scientists and engineers who aspire to solve challenging problems and turn innovative ideas into quality products and services that can help hundreds of millions of users and advertisers, and directly impact our business. 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.
ResponsibilitiesMicrosoft is innovating rapidly in the advertising space to grow its share of this market by providing the ad industry with the state-of-the-art online advertising platform and service. Microsoft's advertising team is at the core of this effort, responsible for research & development of all the algorithmic components in our paid search advertising technology stack, including: Creative Quality Modeling (Clickbait, Perceived/Actual Relevance, Image Quality, Policies etc.) User response (click, wins & conversion) prediction using large scale machine learning algorithms Bidder/Publisher Optimization Advertising metrics and measurement Data mining and analytics Experimentation infrastructure including tools for configuring and launching experiments, dashboard, live marketplace monitoring, and diagnosis. Embody our Culture and Values | |