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Responsibilities
* Design and build user-friendly reports, dashboards, and other decision-support tools (e.g., Power BI/Tableau) to maintain a high level of stakeholder satisfaction, including recurring CPG sales, POS, and customer performance views. * Perform statistical analyses (descriptive, diagnostic, exploratory, correlation, regression, forecasting) to answer business questions such as sales drivers, promotion effectiveness, distribution changes, and retailer/channel trends. * Learn the business and retail landscape to identify novel and impactful applications of Advanced Analytics, including shopper/category insights and store/channel performance. * Support growth of Advanced Analytics and the advancement of the organization's analytic culture by partnering with stakeholders, documenting repeatable processes, and sharing learnings and best practices. * Other duties as assigned.
Desired Experience
* Interest in (or exposure to) CPG and retail analytics concepts such as POS, promotions, distribution, pricing, assortment, and channel/retailer performance. * Ability to follow best practices and quality assurance regarding report design and user experience (clear definitions, consistent metrics, and easy-to-use dashboards). * Foundational understanding of statistical concepts and methods. * Ability to manage multiple requests concurrently using a defined and repeatable process, with strong attention to detail and follow-through. * Strong communication and interpersonal skills, with demonstrated ability to work with cross-functional partners (e.g., Sales, Marketing, Category/Revenue Management, and Supply Chain). * Ability to clearly and concisely communicate analyses, assumptions, and results to a variety of audiences; comfortable turning data into a story and recommendation. * Strong aptitude and drive to continually learn functional areas and data sources (including POS and customer/retailer reporting) to help embed analytics into day-to-day decisions. * Understanding of fundamental analyses and modeling techniques (e.g., time series trends, basic forecasting, driver analysis), with willingness to deepen skills over time. * Experience (academic, project-based, or professional) with analytics tools such as Excel, SQL, Alteryx, Python, R, IBM SPSS, or SAS. * Experience with data visualization tools (Power BI, Tableau, or similar); exposure to CPG/retail datasets (e.g., POS, customer shipment, retailer scorecards, syndicated data) is a plus.
Sprachkenntnisse
- English
Hinweis für Nutzer
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