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<div class="content-intro"><p><span style="font-weight: 400;"><strong>About Faire</strong></span></p> <p>Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.</p> <p>We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.</p></div><p><strong>About this role</strong></p> <p>We're looking for a strong analytical thinker to build and own Faire's Supply Chain and Inventory forecasting for the Fulfilled by Faire program from the ground up. Faire's brands rely on us to be more than a sales channel — we're a business partner. A core part of that means helping brands stay in-stock, manage their inventory effectively, and never miss a sale. As the owner of Supply Chain Analytics, you'll sit at the intersection of data, operations, and brand success. You'll own the translation of our demand forecasting models into concrete, brand-level inventory guidance, monitor the health of brand inventory across the marketplace, and drive meaningful reductions in out-of-stock (OOS) rates that directly influence brands’ sales and success on Faire.</p> <p>This role is for someone who is equal parts data practitioner and problem-solver — someone who loves getting into the weeds of a complex dataset, and isn't satisfied until the insights they surface actually move the needle for thousands of brands.</p> <p><strong>What you’ll do </strong></p> <ul> <li><strong>Own inventory forecasting for Faire's brand base</strong> — translate demand model outputs into actionable inventory replenishment guidance and purchase recommendations for brands.</li> <li><strong>Build and maintain supply chain analytics infrastructure</strong> — develop and own the data pipelines, dashboards, and models that track inventory health, turn rates, and OOS risk across the catalog.</li> <li><strong>Build and maintain demand forecast -</strong> build and own the demand forecast with 3PL warehouse operator so they can drive staffing and forecast planning based on order and inventory volume movements; and to meet our aligned upon SLAs</li> <li><strong>Lead OOS monitoring and intervention</strong> — proactively identify brands and SKUs at risk of going out of stock, quantify the GMV impact, and design scalable interventions (alerts, nudges, tooling) in partnership with Product and GTM.</li> <li><strong>Define and track inventory health metrics</strong> — own key KPIs including OOS rate, inventory coverage, stockout frequency, and false OOS rate; set goals and report progress to leadership.</li> <li><strong>Partner cross-functionally</strong> — work closely with GTM and Ops teams (the primary internal customers of inventory guidance), as well as Data Science and Finance, to ensure outputs are actionable, trusted, and integrated into operational workflows.</li> <li><strong>Develop scalable analytical frameworks</strong> — build reusable models and methodologies for segmenting brands by inventory risk profile and tailoring guidance accordingly.</li> <li><strong>Communicate findings with clarity</strong> — synthesize complex supply chain dynamics into crisp, decision-ready narratives for both operational teams and senior leadership.</li> </ul> <p><strong>Qualifications</strong></p> <ul> <li>3–6 years of experience in supply chain analytics, demand planning, operations analytics, or a closely related analytical discipline.</li> <li>Strong SQL skills — you can independently query large, complex datasets and structure analyses from scratch.</li> <li>Hands-on experience with forecasting or demand planning — you've worked with statistical demand models (e.g., time series, regression-based) and understand how to translate forecast outputs into operational guidance.</li> <li>Proficiency in Python or R (preferred) for data wrangling, modeling, and workflow automation.</li> <li>Comfort with BI and visualizat
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