Principal Data and Applied Scientist Manager at Microsoft

Principal Data and Applied Scientist Manager Details

May 15, 2019, 9:12 p.m.
Individual Contributor
Redmond, WA
Time Management team Time Management team
The Communications and Time Management team powers the email and collaboration products that hundreds of millions of users count on every day to connect, organize, and get things done. Through our rich history of bringing email and calendar together in Outlook we have learned the importance of building products that focus on simplicity, reliability, and creating delightful experiences so everyone can cut through the noise and focus on what matters most to them. We are currently building the next generation of products and features that span our portfolio of our world-class communication applications – Outlook, our flagship email and calendaring brand and Yammer, our solution to help people connect across organizations. Do you love data? Do you love collaborate with teams of customer focused engineers and product managers to unlock insights? We believe in putting our customers first and making sure that everything we do aligns with the jobs our customers hire us for. We focus on delivering

Develop the tools to best drive insights across the breadth of the Outlook as a Service products through both aggregate and real time data streams. Drive a deep understanding of user behaviors across all products and services to empower product managers, designers, and marketers to better target our customers. Driving metrics and measurements development for the products Explore and build new tools to model, test, and drive innovation across our business and customer experiences. Champion the use of data analysis and data Science practices across all aspects of our product and service portfolio
Have a minimum of 7 years of relevant work experience in data-analysis, finance/business analytics related roles. Are able to break down complex business and technical problems into opportunities for analytical study. Have extensive knowledge and experience in data science including expertise in one or more of: finance analysis, business/customer intelligence, machine learning, big data/data mining, statistics, data modeling, information theory, or a similar field. Are inherently curious, energized by large challenges, and interested in making a significant impact on a globally scaled business
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