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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers and products. The company uses machine learning and data insights to revolutionize the wholesale industry, helping local retailers compete against large e-commerce and big-box competitors.
As a Senior Applied AI/ML Scientist on the Retailer team, you will develop and deploy machine learning models that power core business functions. Your work will span three primary areas:
**Shipping Cost Optimization**: Build ML models that provide accurate shipping cost estimates using live carrier information. Engineer new features to improve model performance while maintaining explainability and computational efficiency.
**Underwriting & Credit Risk**: Improve Faire's net terms portfolio by evaluating retailer creditworthiness. Use predictive modeling to dynamically assign credit limits that minimize default risk while maximizing growth opportunities.
**Retailer Growth & Lifecycle**: Build models to automatically generate landing pages and content targeting search engine demand. Apply natural language processing to understand keyword intent and match to relevant internal content. Develop ML models generating retailer intelligence for personalization. Predict retailer lifetime values to optimize acquisition spend.
You'll collaborate closely with data scientists, machine learning engineers, and product managers to unlock value from Faire's unique two-sided marketplace data. The team includes experienced practitioners from Uber, Airbnb, Square, Facebook, and Pinterest.
Required qualifications include an advanced degree (MS or PhD) in statistics, economics, mathematics, computer science, operations research, or related field. You need 3+ years of experience productionizing ML models using tools like Sklearn, XGBoost, or deep learning frameworks. Strong programming skills in Python, Java, Kotlin, or C++ are essential. Knowledge of statistical techniques including experimentation and causal inference is required. SQL or database querying experience is preferred.
The role is hybrid, requiring office presence three days per week (Tuesdays, Thursdays, and one flex day), with flexibility to work remotely up to four weeks annually.
