Senior Applied AI/ML Scientist - Retailer

About the role

Faire is a technology wholesale platform connecting independent retailers worldwide. Its Data Science team builds machine learning models for the marketplace, and the Retailer team focuses on optimizing logistics and freight costs, calculating optimal credit limits, improving SEO, personalizing landing pages for new retailers and predicting retailer lifetime value. The role is based in San Francisco.

Key responsibilities

• Shipping cost optimization: build ML models that give accurate shipping cost estimates, engineer new features to improve performance, and make the models performant and explainable, possibly using live carrier information.
• Underwriting: evaluate the creditworthiness of retailers and use predictive modeling to dynamically assign credit term limits that minimize default risk and maximize growth.
• Retailer growth and lifecycle: build models that automatically generate landing pages and content targeting search engine demand, use NLP to match search keywords to internal content, generate retailer intelligence for personalization, and predict retailer lifetime values to optimize acquisition spend.

Required profile

• An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science or operations research.
• 3+ years of experience productionizing machine learning models.
• Knowledge of statistical techniques such as experimentation and causal inference.
• SQL or other database querying experience preferred.

Required skills

• Machine learning with Sklearn, XGBoost or deep learning.
• Programming in Python, Java, Kotlin or C++.

What we offer

• Salary range of $211,000 to $290,500 per year in California, plus eligibility for equity and benefits.
• Paid time off, company-wide recharge days and paid parental leave up to 16 weeks.
• Health coverage, fertility and family-building benefits, mental health support, professional development stipends and a retirement plan.
• Hybrid work: 3 days in the office (Tuesdays, Thursdays and a flex day), with remote work up to 4 weeks per year.