Data & Applied Scientist ll at Microsoft

Data & Applied Scientist ll Details

Nov. 27, 2018, 9:49 p.m.
Engineering
★★
Individual Contributor
Full-Time
Redmond, WA
and Analytics team Azure Customer Growth
The goal of Azure Customer Growth and Analytics team is to foster a data-driven culture; to encourage and enable the entire organization to make more informed decisions through data. In support of this mission, our Business Analytics team works closely with engineering, marketing, finance, and business leaders to identify opportunities for improving the customer experience and accelerating the growth of our business. Our charter spans the breadth of Cloud + AI, where we design and deliver standardized views of business performance, identify salient trends, perform ad hoc analyses of historical data, define benchmarks and models for predicting upcoming performance, and surface key insights. As the availability of data and demand for analysis grows, we need a capable data scientist to help stakeholders across the organization better understand user behavior and service usage, create compelling offers, and optimize the customer experience.

KEY ACCOUNTABILITIES: Become a subject matter expert in the C+AI business and underlying data ecosystem. Collaborate with product and program owners across the organization to understand objectives, identify opportunities, and inform data-driven decisions. Prioritize projects to maximize business impact. Identify changes in customer behavior, system performance, or financial results, and deliver the necessary insights to explain them and recommend actions to be taken. Deliver accurate and timely standardized reporting and analysis in support of ongoing business reviews and planning processes. Recognize
KEY QUALIFICATIONS: 5-7 years of experience in analytics, business intelligence, or data driven business strategy. Functional knowledge of cloud computing and online services business models, including business, technical, and operational metrics. Demonstrated analytical ability; problem deconstruction, statistical thinking, meticulous forensic analysis skills, data validation, and scientific rigor. Demonstrated stakeholder management ability including effective prioritization, clear concise communication, and delivery of actionable data driven insights. Highly proficient with T-SQL and Excel.
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