Senior/Staff Data Scientist, Storefront

<div class="content-intro"><p><span style="text-decoration: underline;"><strong>ABOUT QUINCE</strong></span></p> <p>Quince is a destination for builders, creators, innovators, and operators who want to come together and challenge the status quo. Our mission is simple: make really high quality essentials for really low prices, fairly and sustainably. We deliver on that mission through a unique manufacturer-to-consumer (M2C) model eliminating the layers of traditional retail that add cost and result in consumers paying more than they need to. We find, build relationships with, and work directly with the manufacturing partners behind some of the world’s finest products. From there, our teams design smart, efficient operational processes  and build and deploy proprietary technology, AI, and analytics to help us scale fast.</p> <p>What began with a small assortment of elevated basics has quickly grown into a cross-category brand spanning apparel, accessories, home goods, and more. Today, tens of millions of people across a growing number of countries come – and return – to Quince because they trust us to deliver.</p> <p><span style="text-decoration: underline;"><strong>OUR CULTURE</strong></span></p> <p>Quince is a culture built for builders by builders. Our way of working starts with a blank sheet of paper. We question conventional thinking, use technology and data to uncover new opportunities, and move quickly to turn ideas into reality. We aren’t interested in replicating how others do retail. We’re building a better way – at a speed and scale unlike anything that’s been done before.</p> <ul> <li>We dream big and chase the hard problems others shy away from. Rejecting long-held assumptions is part of our company's DNA.  Where conventional wisdom says you have to choose – soft or durable, speed or rigor, quality or price – we ask why that trade-off has to exist in the first place.</li> <li>Our pace is fast and the bar is high because our customers expect a lot from us and we refuse to let them down. We believe the best results come from challenging ourselves, learning from one another, and building on each other's strengths. </li> <li>Here, responsibility is not determined by role, tenure, or seniority. Every team member - no matter their level - has the opportunity to drive our business and shape our trajectory. </li> </ul> <p>If you’re someone who likes to imagine new possibilities and build better systems rather than plug-in to outdated ones, Quince is the place for you.</p></div><p data-renderer-start-pos="2290" data-local-id="6a0d0d38-3057-4834-9012-12f09f19e465"><strong data-renderer-mark="true"><span class="fabric-text-color-mark" data-renderer-mark="true" data-text-custom-color="#0747a6"><u data-renderer-mark="true">THE ROLE </u></span></strong></p> <p><strong>Senior/Staff Data Scientist, Storefront</strong></p> <p>We are seeking a highly analytical and technical <strong>Data Scientist</strong> to join our Storefront team. In this role, you will own end-to-end modeling work across high-priority surfaces — spanning Recommendations and Personalization, Search, and AI-powered Shopping Experiences — and your contributions will have direct, measurable impact on conversion, discovery, and user satisfaction at scale. You will report to our VP of Engineering and collaborate closely with engineering managers, software engineers, and product managers to move our capabilities from traditional models into near real-time, personalized, and Generative AI-driven experiences. </p> <p><strong>Responsibilities</strong></p> <ul> <li><strong>Real-Time Personalization:</strong> Go beyond static product recommendations to develop and refine machine learning models that deliver near real-time personalization across our app and site surfaces, leveraging contextual signals to customize text and details for varied buyer intents (e.g., price-sensitive vs. quality/sustainability-first buyers).  </li> <li><strong>In-House Search Platform</strong>: Assist in building our natural language search engine from 0 to 1, utilizing Large Language Models (LLMs like Claude and GPT) for query understanding, semantic search, and advanced language retrieval.  </li> <li><strong>App Engagement: </strong>Design and implement algorithms for interactive app experiences to drive daily customer engagement.  </li> <li><strong>End-to-End Pipeline Ownership:</strong> Create new relevance ranking features, build automated end-to-end modeling pipelines in Python and SQL, deploy ML models into production, and run rigorous live experiments.  </li> <li><strong>Data Infrastructure & Tooling:</strong> Identify data gaps, write clear data product specifications, and partner with Engineering to establish robust real-time tracking and performance monitoring frameworks.  </li> <li><strong>Cross-Functional Partnership:</strong> Act as a technical partner to product and business squads, translating business targets into actionable data science solutions and presenting complex analytical outcomes to leadership. </li> </ul> <p><strong>Qualifications</strong></p> <p><strong>Required:</strong></p> <ul> <li>2+ years of industry experience as a data scientist, with a strong preference for consumer-facing products or e-commerce applications operating at high scale.  </li> <li>MS or PhD in statistics, mathematics, engineering, computer scie