Data Science Intern

Data Science Internship — Multiple Teams

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.

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.

Our internships are paid, 12–14 weeks in duration, with flexible start dates. Extensions are considered based on project scope and mutual interest.

Open Teams

Search & Recommendation

• Design and deploy state-of-the-art recommender systems that power ranking and discovery across the marketplace
• Develop rich user and item representations through embeddings, sequence models, and graph-based methods
• Build real-time and streaming data pipelines that enable dynamic, context-aware personalization at scale
• Apply exploration–exploitation strategies — including contextual bandits and reinforcement learning — to optimize recommendations under uncertainty
• Advance recommendation quality through improvements to diversification, novelty, and long-term user engagement
• Own the full ML lifecycle: from problem formulation and modeling through offline evaluation and online experimentation

Risk Management

• Build and refine models and heuristics across core risk domains — including underwriting, identity verification, returns, markdowns, and disputes & misuse — to reduce financial losses and unlock GMV growth
• Partner cross-functionally to develop scalable, data-driven frameworks that balance risk exposure with business opportunity

What You'll Do

• Design, develop, and A/B test cutting-edge machine learning algorithms and analytical solutions, with guidance from senior technical leads
• Communicate project objectives, methodologies, and results clearly to both immediate teammates and broader cross-functional stakeholders
• Navigate the complexity of a two-sided marketplace, identifying and addressing the unique challenges that arise at the intersection of retailer and brand needs

What We're Looking For

All candidates must be currently enrolled or recently graduated Master's or PhD students in Computer Science, Operations Research, Statistics, Econometrics, or a related technical discipline. Beyond that, we're looking for team-specific experience: