Retail Data Scientist Join a global analytics and planning team driving decisions across the full retail lifecycle. This group builds scalable systems and delivers actionable insights that support assortment planning, brand development, and global retail operations. As a Retail Data Scientist, you will manage, explore, and engineer large datasets to deliver business-critical insights using advanced data science techniques and predictive modeling. Your work will directly influence pricing, planning, and merchandising strategy at scale. What You’ll Do: • Translate business questions into structured analytics and deliver actionable insights to merchandising, planning, and pricing teams • Partner with merchandise planners, business stakeholders, and technical teams to frame problems and define project scope • Analyze large datasets to identify trends in sales, inventory flow, price performance, and promotional effectiveness • Create tools, models, and reporting pipelines to improve pricing strategies, liquidation decisions, and SKU optimization • Design dashboards and data products using Tableau, Excel, SQL, and Python (or similar tools) • Support the configuration and enhancement of packaged retail applications and data workflows • Develop executive-level presentation materials and business summaries • Manage and prioritize a queue of enhancements, issues, and project requests from partners • Lead root cause analysis and develop solutions to ensure consistent, scalable data output What You Bring: • 5+ years of analytics experience, preferably in a retail, consumer goods, or inventory-based environment • Strong SQL and data wrangling skills; comfort working with large and sometimes incomplete datasets • Experience with pricing models, promotional strategy, markdown/liquidation analysis, or merchandise planning • Fluency in tools like Tableau, Excel, and Python/VBA for building dashboards, automations, and data products • Ability to communicate technical findings to non-technical audiences and influence decision-makers • A proactive and collaborative approach to solving problems in a cross-functional setting Additional Requirements: • Bachelor’s degree in Computer Science, Engineering, Math, Statistics, or a related field; equivalent work experience will also be considered • Must be authorized to work in the United States without current or future sponsorship • Must be available to work onsite in Orlando, FL a minimum of four (4) days per week as part of a hybrid schedule