Senior Business Analytics Specialist, Services Insights, Microsoft Services at Microsoft
Senior Business Analytics Specialist, Services Insights, Microsoft Services Details
Jan. 4, 2019, 6:32 p.m.
Business Programs & Operations
Individual Contributor
Full-Time
Issaquah, WA
The Services Insights
Do you have a passion for and a desire to shape the business insights into a competitive differentiator and elevate to the next level in business intelligence? Desire a pivotal role in the transformation of BI capability for a global business that is immersed in Microsoft's full product and services catalog? Are you looking for an opportunity to work with a great team in a high impact position? We're looking for a talented professional to join our team! The Services Insights function endeavors to foster an insights-driven culture; to encourage and enable positive business outcomes across the organization by driving right behaviors and decisions through bold insights. This team understands the business goals, strategic drivers, success outcomes and associated behaviors. You will partner to meet a spectrum of demand across insights, analytics, decision-boards and scorecards. Your passion and desire to define and enact the vision for insights and analytics will shape this function into a competitive
Build and develop analytical models working alongside a strong team of Leads, Analysts, Architects to deliver priority outcomes in alignment with the strategic roadmap for Services Engage broadly with the Decision Science teams to frame, structure and prioritize business problems where insights can have the biggest impact Act as an evangelist and catalyst for BI and Analytics innovation Manage the portfolio of work for BI and Analytics and partner with decision science team on monthly governance with stakeholders Partner on a robust, sustainable cloud first big data architecture, data lake, data
Basic qualifications will be 7+ years including experience in the following: 7+ years in Statistics - Basic probability distributions, estimation techniques, confidence intervals, hypothesis testing (z-test, t-test, ANOVA, etc.) Understanding of Maximum Likelihood Estimation is a plus 3+ years in Machine Learning - Regression, Classification, Clustering, Data preparation (outlier treatment, missing value imputations etc.), Feature engineering (polynomial, log and other functional transformations), Feature selection, Time series, Text Mining and Model interpretation through Decision Trees, Linear