Are you interested in working for one of the most exciting products in Microsoft, passionate about exceeding customer expectations and advancing Microsoft's cloud first strategy? Are you interested in a start-up like environment, excited about cloud computing technology and driving growth in one of Microsoft's core businesses? If so, then look no further than the Azure Customer Experience (CXP) Team! Microsoft Azure provides customers with an on-demand and infinitely scalable infrastructure and platform for customers to build, host, and scale service applications on the Internet through Microsoft's global data centers. As part of the Azure Engineering organization, Azure CXP is a rapidly growing team committed to driving Azure growth through our relentless pursuit of satisfied Azure customers, by leading world-class customer reliability engagements, engineering modern customer-first experiences for scale, and by driving deep customer insights and empathy into the broader Azure Engineering
Work with management and stakeholders, identify opportunities for data science to make an impact, and formulate these opportunities to data science projects. Identifies data sources, integrates multiple sources or types of data, and applies expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data Applies (and develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis Transforms formulated problems into implementation plans for experiments by applying (and creating when
M.S. (Ph.D. Preferred) in Computer Science, Statistics, Operations Research or similar quantitative field Solid foundation of machine learning algorithms (classification, regression, clustering, time series forecasting, recommender system, text analytics). Experience with deep learning is a plus. Working experience in applying machine learning to one or more of the following fields (forecasting, text analytics, customer CRM, transactional analytics, etc). Deep understanding of big data systems, including Spark, Hadoop, Azure Data Lake, Cosmos, Azure SQL, etc. Expert in one or more machine learning