Senior Applied AI/ML Scientist - Retailer
AI summary of the role
Senior Applied AI/ML Scientist on the Retailer team at Faire, a wholesale marketplace.
What you’ll do
- Build ML models for shipping cost optimization using live carrier information, ensuring performance and explainability.
- Improve Faire’s Net terms portfolio by evaluating retailer creditworthiness and dynamically assigning credit limits.
- Develop models to automatically generate landing pages and content for search engine demand using NLP.
- Predict retailer lifetime value to optimize acquisition spend.
What you’ll bring
- Advanced degree (MS or PhD) in statistics, economics, mathematics, computer science, operations research, or related field.
- 3+ years experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning).
- Strong programming skills in Python, Java, Kotlin, or C++.
- Knowledge of statistical techniques including experimentation and causal inference.
Technologies
Sklearn · XGBoost · Deep Learning · Python · Java · Kotlin · C++ · SQL · NLP
About Faire
Wholesale marketplace connecting independent retailers and brands with discovery, ordering, payments, logistics, and inventory tools in one platform.
Series G · 1000–2000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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 team, you'll tackle a diverse set of challenges, such as optimizing logistics and freight costs and calculating optimal credit limits. You'll also contribute to growing Faire’s
More from the job description
About Faire 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. 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 [... source excerpt omitted ...] f 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 team, you'll tackle a diverse set of challenges, such as optimizing logistics and freight costs and calculating optimal credit limits. You'll also contribute to growing Faire’s retailer base by enhancing Search Engine Optimization, personalizing landing pages for new retailers, and predicting retailer lifetime value. 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. [... source excerpt omitted ...] ists 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 creditworthiness of retailers on Faire’s platform. Use predictive modeling to dynamically assign credit terms limits that minimize default risk and maximize growth. Re
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