The Data Analyst supports the coordination, gathering and execution of seasonal customer-facing product data, attributes and assets to drive selling initiatives in support of the business. Coordinates the handling and execution of Clarks Americas customer-facing product data to ensure data dependencies and deadlines are met in a timely manner based on business needs and seasonal selling calendars. Manages item setup and data management for key drop ship accounts in collaboration with Sales as well as auditing assortment to recognize opportunities and drive additional revenue.
1. Sales Teams and Wholesale Customers supported with seasonal and as-needed data and assets required for drop ship channel.
2. Approved assortments and corresponding data feeds are in place in support of drop ship programs.
3. Effective relationships in place and utilized to synchronize the flow of data.
4. Manage approval and onboarding of new Drop Ship/E-Com customers
5. Analysis of Drop Ship forecast, selling & productivity analysis (operational lens)
6. Analysis and engagement surrounding customer-facing transactional readiness data.
7. Business supported in planned and ad-hoc projects and digital shelf initiatives
Skills, Knowledge and Experience:
• A minimum of 1-2 years’ experience in an analytical and reporting capacity
• Experience managing data
• Experience working with confidential information and within a highly regulatory environment
• Proven cross functional collaboration
• Strong written & verbal communication skills
• Strong analytical and organizational skills; keen attention to detail
• Proficiency in Microsoft Excel is required, other Office applications desired
• Must be a self-starter capable of delivering results and achieving goals effectively and efficiently with minimal supervision
• Analytical and able to identify key information
• Problem solving skills
• Excellent interpersonal skills
• Team player, goal-oriented
• Customer Focus
• Effective Decision Making
• Strong ability to multi-task and support multiple initiatives running concurrently