<p>Who We Are: Schwazze (SHHwahZZ) is a purpose-driven, vertically integrated cannabis operator. We are building a leading seed-to-sale company with best-in-class dispensaries and exceptional cultivation, manufacturing, and wholesale capabilities. Driven by a high-performance culture, we combine customer focus and data-driven insights to unlock the plant's full potential and improve the human condition.</p> <p>At Schwazze, you are not just an employee-you are part of a purpose-centered, performance-driven team where your contributions matter, your growth is supported, and your potential is limitless. We lead with integrity, connection, engagement, excellence, and empowerment, fostering a culture where people thrive, communities flourish, and the industry moves forward. These values define our commitment to creating a supportive, positive workplace while delivering exceptional customer experiences.</p> <p>For more information, please visit our website: www.schwazze.com</p> <p>Job Title: Merchandising Analyst</p> <p>Salary Range: $70,000-$80,000</p> <p>Type: Full-Time, Exempt</p> <p>Location: Denver, Colorado (Main Office) | Boulder, CO (Satellite Office)</p> <p>Position Objective</p> <p>The Merchandising Analyst serves as a critical analytical and operational support partner to the Merchandising organization, enabling data-driven decision-making across categories, banners, and markets. This role is responsible for ensuring data accuracy, producing actionable insights, and supporting category performance through reporting, pricing analysis, inventory visibility, and vendor evaluation. This individual must understand how to gather data and provide critical performance insights at an executive level, including product performance assessment, shelf space value analysis, identification of dying products, and recommendations for category gaps and benchmarking demand.</p> <p>Essential Functions</p> <p>Data Management & System Support (25%)</p> <ul> <li>Maintain and support the backend data infrastructure for merchandising and retail reporting, ensuring data integrity across systems, banners, and categories </li><li>Support data migration, normalization, and validation efforts related to mergers, acquisitions, and system integrations </li><li>Maintain and update master category and item files, including pricing, cost, margin targets, tiering, and inventory guidelines </li><li>Ensure accuracy and consistency of data used in dashboards, reports, financial summaries, and category reviews </li><li>Serve as a point of coordination for resolving data discrepancies between POS, inventory, finance, and merchandising systems </li></ul> <p>Reporting & Analytical Support (35%)</p> <ul> <li>Analyze sales, margin, inventory, and promotional performance across categories to identify trends, risks, and growth opportunities </li><li>Build, maintain, and enhance recurring scorecards, dashboards, and KPIs including sell-through, inventory turns, aging, margin mix, and promotional ROI </li><li>Support pricing analysis using competitive benchmarks, internal performance data, and market intelligence tools (e.g., BDSA or similar) </li><li>Provide analytical support for assortment frameworks such as Good/Better/Best, tiered pricing, and category role definitions </li><li>Deliver clear, concise insights to Category Managers and leadership to inform decisions and recommendations </li></ul> <p>Category & Vendor Support (25%)</p> <ul> <li>Partner closely with Category Managers to support SKU rationalization, category strategy execution, and new item launches </li><li>Evaluate vendor performance, pricing changes, cost structures, and promotional activity using standardized scorecards and metrics </li><li>Support vendor negotiations and line reviews by preparing data, analyses, and performance summaries </li><li>Assist with assortment resets, category transitions, and promotional planning through analytical preparation and post-event analysis </li></ul> <p>Process Improvement & Tool Development (15%)</p> <ul> <li>Support the standardization and continuous improvement of merchandising reporting, analytical tools, and workflows </li><li>Assist in developing scalable reporting frameworks that support growth across multiple banners and markets </li><li>Improve data visualization, automation, and reporting efficiency to reduce manual effort and increase insight velocity </li><li>Contribute to best-practice merchandising analytics that enable consistency, transparency, and accountability </li></ul> <p>Critical Analytical Competencies:</p> <p>Executive-Level Insight Generation</p> <ul> <li>Translates complex data into clear, actionable insights that executives can use to make strategic decisions </li><li>Identifies key performance drivers and risks without being asked, proactively surfacing critical issues </li><li>Presents findings with business context and recommended actions, not just data dumps </li><li>Tailors communication style and level of detail to audience (executives need different insights than category managers) </li></ul> <p>Product Performance Assessment</p> <ul> <li>Assesses product performance at granular levels: SKU, banner, store, time period </li><li>Identifies products that are dying (declining sales velocity, aging inventory, compressed margins) </li><li>Analyzes contribution margin by product to understand true profitability, not just revenue </li><li>Tracks product lifecycle patterns and signals when items need promotional support, repositioning, or discontinuation </li><li>Compares performance across banners to identify execution gaps or assortment opportunities </li></ul> <p>Shelf Space Value & Assortment Optimization</p> <ul> <li>Calculates sales per square foot and dollars per linear foot to optimize space allocation </li><li>Identifies low-productivity SKUs that are consuming valuable shelf space </li><li>Recommends space reallocation based on category growth, margin contribution, and customer demand </li><li>Analyzes adjacencies and cross-sell opportunities to inform merchandising placement strategies </li><li>Supports planogram optimization with data on product velocity and basket attachment </li></ul> <p>Category Gap Analysis & Demand Benchmarking</p> <ul> <li>Identifies missing items in categories by comparing assortment to competitive benchmarks and market data </li><li>Uses external benchmarking data (BDSA, competitor shopping) to quantify assortment gaps and opportunities </li><li>Analyzes customer behavior and search patterns to identify unmet demand </li><li>Recommends new item introductions based on market trends, competitive activity, and category strategy </li><li>Quantifies the financial opportunity of closing assortment gaps (estimated incremental revenue and margin) </li><li>Tracks category performance against market benchmarks to measure share capture and competitive positioning </li></ul>