Data Science Intern

<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 class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><strong>Data Science Internship — Multiple Teams</strong></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e-commerce platforms and big-box stores. Our Data Science team builds and maintains the algorithmic systems — spanning search, personalization, recommendation, and ranking — that power our marketplace and help our customers thrive.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">We are hiring Data Science interns across several teams and are looking for intellectually curious, self-directed problem solvers eager to work end-to-end on high-impact challenges, from data exploration to production-ready solutions.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]">Our internships are paid, 12–14 weeks in duration, with flexible start dates. Extensions are considered based on project scope and mutual interest.</p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><strong>Open Teams</strong></p> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><em><strong>Search &amp; Recommendation</strong></em></p> <ul class="[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3"> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Design and deploy state-of-the-art recommender systems that power ranking and discovery across the marketplace</em></li> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Develop rich user and item representations through embeddings, sequence models, and graph-based methods</em></li> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Build real-time and streaming data pipelines that enable dynamic, context-aware personalization at scale</em></li> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Apply exploration–exploitation strategies — including contextual bandits and reinforcement learning — to optimize recommendations under uncertainty</em></li> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Advance recommendation quality through improvements to diversification, novelty, and long-term user engagement</em></li> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Own the full ML lifecycle: from problem formulation and modeling through offline evaluation and online experimentation</em></li> </ul> <p class="font-claude-response-body break-words whitespace-normal leading-[1.7]"><em><strong>Fulfillment</strong></em></p> <ul class="[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3"> <li class="whitespace-normal break-words pl-2" style="font-style: italic;"><em>Develop ML models that predict product demand for brands leveraging Faire's fulfillment services, informing replenishment decisions, reducing stockouts, and improving invento