Lead Insights and Analytics Manager - NIKE Retail Services Inc - Beaverton, OR. Drive scalable and sustainable impact from our analytics capabilities. Build recommendations that reveal the opportunities where our elevated store concepts and services are uniquely placed to attract and retain consumers. Translate complex analytics into concise stories for the business and familiar with retail consumer trends for premium brands. Understand the role membership programs & services play in driving value for direct-to-consumer brands. Act as consumer advocate for our Nike Direct Stores. Partner with leadership to deliver insights and recommendations to serve our Nike Direct consumers and their evolving needs. Profile our Nike Direct store consumer and their relationship with our premium products, leading to optimized strategies to deliver value to these consumers and the Nike business. Implement a test and learn offense. Deliver solutions and education that empower business stakeholders to self-serve. Sit within a centralized Analytics & Insights function for North America and serve as a well- rounded Nike Direct Stores data. Insights expert, report to the Directors of Nike Direct Inline Store Analytics and Nike Direct Value Store Analytics. Partner with Nike Direct store leaders to help that team create, deliver & optimize world class retail experiences through innovative retail concept, connected services, and distinctive Nike experiences. Partner closely with cross-functional analytics teams to create and implement scalable insights to drive consumer engagement and growth in North America. Telecommuting is available from anywhere in the U.S., except from AK, HI, MT, NC, ND, SD, VT, and WY. 

Employer will accept a Master’s degree in Business Administration, Data Analytics, Business Analytics and Project Management or Engineering and 2 years of experience in the job offered or in an analytics-related position.  
 

• SQL 

• Python programming 

• R Statistical language  

• Time series forecasting  

• Campaign analysis (A/B Testing)  

• Business intelligence platforms (Snowflake) 

• Data visualization (Power BI, Tableau, Looker)  

• Data manipulation using advanced Microsoft excel  

• Data analysis 

• Predictive modelling  

• Cloud-based big data platforms (Databricks, Domino) 

• Business communication tools (Powerpoint / Keynote)