Senior Manager, Merchandising Analytics

REI Co-op works together to find better ways to work. The goal is to help people enjoy the outdoors. Working for the co-op means doing your best work. Support is given to help you live your best life. You also help shape the future of the outdoors for people and the planet.

This role contributes to REI’s success by owning the data analytics and data science efforts for the Merchandising Product organization that spans the enterprise. Leading a team of Merchandising analysts, the individual in this role will work within Merchandising and across the co-op to develop and apply advanced analytics techniques designed to identify product and assortment optimization opportunities. Near-to-long-term strategies will be influenced by this role and their team by way of the data-driven methodologies and analytics workstreams and assets they will be accountable for creating and disseminating. Critical co-op ambitions like market share and customer growth, assortment productivity, activity initiatives, and the like will be informed and influenced by this role’s contributions and thought leadership.   

The Sr Manager, Enterprise Product Analytics, will collaborate with cross-functional leaders and team across the co-op including those in Strategy, IVC, Customer Planning, Finance, and IT to ensure data and analyses are developed, consumed, and articulated in ways that enable meaningful action within functional working teams. Analytics developed by this role and their team will be designed to illuminate opportunities to drive profitable business growth. This role will act as a trusted partner in the continuous evolution of REI’s data science platform and technology through partnership with IT and other data and analytics divisions. They will be accountable for workflow improvement processes that enable product delivery and analytical modeling at scale. Models and acts in accordance with REI’s guiding values and mission.  

Leading the Way

• Identifies and communicates key responsibilities and practices to ensure the organization promotes a successful attitude, confidence in leadership, and teamwork to achieve business results. 
• Supports the implementation of company programs, procedures, methods, and practices to promote key Co-op initiatives and strategies.
• Challenges and inspires employees to achieve business results.
• Ensures employees adhere to legal and operational compliance requirements.
• Oversees training and development of employees directly and indirectly managed and makes effective staffing decisions.
• Nurtures and supports team-member career growth aspirations. Conducts and ensures the completion of performance reviews.
• Provides coaching, direction, and leadership support to employees to achieve department, company and customer results.
• Ensures team of direct reports are kept current regarding REI’s strategic initiatives and best practices. 
• Responsible for hiring and building a team that exemplifies REI’s Values in Action.
• Establishes and maintains visibility within the department. 
• Monitors operational statistics, reports trends, variances, issues, and takes appropriate action.
• Understand REI strategic plan and linkages to product and assortment analytics and support implementation of solutions that drive results. 
• Contribute to the near-and-long-term Merchandising product and assortment strategic and business plans. 
• Understand, fully use, and continuously improve processes and systems. 
• Monitor and digest competitive industry analytics trends.  

Responsibilities

• Deliver data analysis and data science insights and implications through the product and assortment lenses that supports and guides strategic thinking and systemic performance. 
• Create analytical models and decision-making frameworks that drive product and assortment optimization in an integrated, omnichannel capacity.
• Lead a team of advance analyst professionals, focusing on both business results and employee mentoring and professional development.
• Manage the Merchandising product data warehouse from a business perspective to define data sources, metrics, dimensions, and dashboards to support regular reporting and ad hoc inquiry. Collaborate with the IT organization to ensure good data hygiene and integration across sources.
• Develop and implement roadmap for data mining and quantitative methods to advance product and assortment optimization, productivity measurement, market share growth opportunity, and other key business workstreams and initiatives.  
• Partner with cross-functional teams to leverage product and assortment intelligence to drive and optimize the customer experience and revenue growth opportunities through operations-focused tactics and through go-to-customer methods.
• Engage and influence divisional leaders and executives with data-driven strategic recommendations based on advanced analytics.
• Lead and implement development of Merchandising product and assortment test and initiatives measurement.  

Qualifications

• MS required, graduate degree in quantitative fields of Mathematics, Statistics, Econometrics, Operations Research, Industrial Engineering or other Engineering field  preferred
• 10+ years of work experience in data analysis or data science 
• 5+ years demonstrated leadership/management skills with reporting analytics/data science functions
• 10+ years of experience and expertise developing, testing, and deploying data science and optimization models and visualizations both locally and in a hybrid environment. Proficiency in SQL and at least one programming language such as R or Python
• Proficiency in SQL and at least one programming language such as R or Python 
• Comfortable and effective when communicating with director and VP-level business leaders. Strong ability to understand business and operations problems and translate to research initiatives
• Experience managing/leading analysts in delivery of predictive and/or prescriptive models at speed/scale
• Strong time management and prioritization skills with ability to manage multiple projects simultaneously