The Retail Business Analyst 2 will play a critical role in driving relevant and actionable business initiatives for Living Spaces. This position will be responsible for designing, testing, and maintaining data integration, transformation, and quality processes, ensuring efficient use of data across teams and platforms. By leveraging data insights, the Business Analyst will contribute to elevating Retail Operations' proficiency and efficiency. Collaborating closely with the Retail Analytics Manager, they will devise an effective strategy for data collection, analysis, and reporting to support the business needs. Position Description Essential Duties and Responsibilities include the following. Other duties may be assigned. Architect, build, and launch intuitive data models that provide actionable insights for stakeholders across Living Spaces. Determine the optimal data architecture to ensure seamless data integration, distribution, and analysis for Living Spaces' business data domains. Work across multiple teams in high-visibility roles, taking ownership of solutions end-to-end. Organize, mine, and analyze massive structured and unstructured data sets to identify trends, patterns, and insights that aid critical decision-making for Living Spaces. Develop and optimize the business metrics data layer for scalability, reliability, and resilience. Act as a thought-leader in analytics and data science, particularly in entity resolution concerning Living Spaces' business goals. Explore data in an unstructured environment and uncover meaningful trends that drive business value for Living Spaces. Generate and maintain a variety of reports and formats (spreadsheets, tables, charts, graphs, dashboards, etc.) and create ad hoc reports as required. Manage the data used for efficient scheduling through Reflexis, including loading correct Reflexis drivers and setting up new store Reflexis accounts. Validate workload management and alignment to payroll budgets and revenue. Mine data by importing, cleaning, transforming, and validating data from various sources (e.g., Excel, Tableau, Alteryx, and other statistical tools). Create additional data collection methods as needed, including the use of Office 365. Analyze, forecast, and model data to reveal business needs and make informed decisions. Craft and deliver compelling, easily digestible data presentations. Support implementation in store operations to assist stores in meeting KPI goals. Build effective partnerships with other departments, including Retail Support Team, IT, Logistics, Marketing, E-commerce, Guest Services, and Purchasing.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
501-1,000 employees