Jobs

Contact: Christy Hentges (christyh@microsoft.com)

Are you looking for a high impact position that will leverage your analytical and project management skills? If you excel at delivering and communicating marketing data analysis, and want to influence the expanding future of relationship marketing at Microsoft, then this position is for you. This is an exciting opportunity, in a growing group, to bring business intelligence to marketing partners at Microsoft and directly affect the strategy and execution of marketing programs.

The goal of the CRM Analytics group is improve customer satisfaction and the quality of Microsoft's customer relationships by taking data and turning it into information from which to build business intelligence. These projects range from testing the effectiveness of customer communications, deep analysis of key customer segments, assisting in new product launches, identifying good customer candidates for new programs, and understanding the key drivers of overall customer satisfaction and profitability. The Senior Analytics Project Manager will

• Work with marketing partners, vendors, and other CRM teams
• Leverage Microsoft's vast data asset
• Combine these with proper analytic techniques
• Deliver customer insight and actionable change to marketing strategy

• Elicit analytic requirements
• Guide data assessments
• Prescribe data collection and measurement practices
• Identify the most relevant analytic techniques
• Guide the primary data analysis
• Develop and present actionable insight

The successful candidate will bring at least 6 years of experience in analytics and business intelligence, with proven project management skills. Solid written, verbal and analytical communication skills are a must as is the ability to communicate and work effectively throughout project teams, vendor partners, and customer groups at all levels of management.

Since guiding marketing programs though the analytic process and identifying relevant tools and techniques are key components of this position, the successful candidate is expected to have exposure to a broad range of data analysis tools and techniques. Understanding the capabilities, limitations, and application of these techniques is more important than understanding the detailed algorithms (although in-depth expertise in two areas is required.) Areas of expected exposure include the following:

• Database principles
• SQL
• OLAP (e.g., BRIO, Cognos)
• Excel pivot tables
• Test/control principles
• Statistical analysis (e.g., significance tests, linear regression)
• Clustering
• Campaign targeting
• Churn analysis