Data Analyst Category Management Job Details Job Location Corporate Headquarters (Sewell, NJ) - Sewell, NJ Position Type Full Time Salary Range $62000.00 - $72000.00 Salary Job Shift Day Job Category Purchasing - Procurement Description About Us/Company Overview: For over six decades, the Delaware Valley Floral Group (DVFG) has been at the forefront of providing professional retail florists, event designers and supermarkets across the nation with the highest quality of fresh cut flowers, greens, botanicals, and floral supplies. Established in 1959 as a modest family venture, the DVFG has flourished into one of the largest floral distribution companies in the United States. Our modern corporate headquarters, spanning over 100,000 square feet, is strategically situated in Sewell, New Jersey. Complementing this central hub are multiple satellite logistics, distribution and sales facilities located in key geographical regions, including Edison, NJ, Jessup, MD, Hauppauge, NY, Syracuse, NY, Hartford, CT, Wilkes-Barre, PA, Shrewsbury, MA, Pittsburgh, PA, Cleveland, OH, Richmond, VA, Miami, FL and Oxnard, CA. Our mission extends beyond just being a floral wholesaler to our customers;We Aspire To Be Their Most Valuable Supplier. Every member of our team plays a pivotal role in ensuring our customers receive the best possible products and services to help their business grow. We recognize that our employees are the cornerstone of our success as well, which is why we are committed to fostering a family-oriented culture where every individual's contributions are deeply valued and appreciated. Join us in shaping the future of floral distribution and become a part of our dynamic team here at the DVFG! We’re looking for a data-savvy and curiousData Analystwith 3–5 years of experience to join our Fresh and Supplies Goods category team. In this role, you'll help improve forecasting, pricing, inventory, and promotional strategies by building and refining analytical models. You’ll play a key part in shaping smarter, more data-driven decisions — with the opportunity to grow your skills toward more advanced analytics and AI/ML integration over time. Key Responsibilities 1. Demand Forecasting Support + Build and maintain sales forecasting models at the SKU and category level. + Use historical trends, seasonality, promotions, and other factors to improve forecast accuracy. + Work with business teams to turn their needs into practical forecasting tools. 2. Pricing & Margin Analysis + Support pricing decisions by analyzing costs, competition, and product performance. + Help design and test simple pricing models that align with margin and inventory goals. 3. Inventory Insights + Analyze inventory patterns and shelf-life data to reduce shrink and improve stock levels. + Assist in building tools to flag overstock risks and recommend timely actions. 4. Promo Performance Tracking + Analyze how promotions impact sales and margins using historical and real-time data. + Support the team in identifying the best timing and products for future promotions. 5. Reporting & Dashboards + Create dashboards and reports using tools like Power BI, Tableau, or Python Dash. + Summarize data findings in a clear, actionable way for non-technical stakeholders. 6. Opportunity to Grow with AI/ML + Contribute to early-stage projects that explore machine learning for demand forecasting, pricing, and inventory management. + Learn and experiment with newer tools and approaches as we evolve our analytics. 7. Collaboration Across Teams + Work closely with category managers, sourcing, marketing, and supply chain teams. + Help others understand and use data insights to guide everyday decisions. Physical Demands: This is an office-based position with extended periods of computer use. Light physical activity such as lifting or filing may occur. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Qualifications + Bachelor’s degree in Data Science, Statistics, Math, Computer Science, or a related field. + 3–5 years of experience in data analysis, preferably in retail, wholesale, or supply chain settings. + Comfortable working with statistical models (e.g., time series, regression). + Strong SQL skills; able to work with large datasets. + Experience with BI tools like Power BI or Tableau. + Curious, collaborative, and able to communicate findings clearly to non-technical teams.