Senior Data Scientist

About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. 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 that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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.

About this role

Faire leverages the power of machine learning (ML) and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and Lifetime Value (LTV) predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.

As a Data Scientist on the Retailer or Brand team, you'll tackle a diverse set of challenges, such as optimizing freight costs, calculating optimal credit limits, personalizing landing pages for new retailers, predicting brand and retailer lifetime value, and improving product listings using AI. You'll collaborate closely with other data scientists, engineers, and product managers to drive projects that unlock value from our unique, rich, and rapidly growing two-sided marketplace data.

Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there! 

What you’ll do 

• Shipping cost optimization: Build ML models that provide accurate shipping cost estimates. Engineer new features to improve model performance. These models may use live carrier information and be both performant and explainable.
• Underwriting: Improve Faire’s Net Terms portfolio by evaluating the creditworthiness of retailers on the platform. Use predictive modeling to dynamically assign credit limits that minimize default risk while maximizing growth. Leverage ML models to improve the retailer Identity Verification (IDV) experience, reducing default losses for new retailers.
• Retailer Growth: Build models to automatically generate landing pages and content to target search engine demand. Use natural language processing to understand search engine keyword intent and match to relevant internal content. Build ML models to generate intelligence about retailers to power personalization. Predict retailer lifetime values to optimize retailer acquisition spend.
• Brand Growth: Prioritize brand leads for sales by predicting their lifetime value. Estimate the incremental value of new brands based on Faire’s existing selection and brand characteristics. Optimize how new brands are featured and explored.
• Listing Quality and Catalog Growth: Use AI techniques to detect and correct image issues, generate product titles and descriptions, extract product attributes, and predict product taxonomy. Perform entity resolution in order to match products across multiple data sources and link product variants.
• Marketplace Quality: Summarize and tag retailer reviews using LLMs. Detect and remove products that violate Faire’s policies, such as counterfeits. Use marketplace levers to direct retailers toward brands with higher service quality.

Qualifications

• An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.
• Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning)
• Strong programming skills (Python, Java, Kotlin, C++)
• Knowledge o