{"id":"3u20922501","title":"Senior Applied AI/ML Scientist - Retailer","posted_at":"2026-05-01T18:51:21.000Z","apply_url":"https://job-boards.greenhouse.io/faire/jobs/7953217002","locations":["San Francisco, CA"],"employment_type":"full_time","workplace_type":null,"seniority_level":"senior","description_language":"en","source_name":"greenhouse","source_url":"https://boards.greenhouse.io/faire/jobs/7953217002?gh_jid=7953217002","salary":{"min":211000,"max":290500,"currency":"USD","period":"year","display":"$211,000–$290,500"},"job_summary":"Faire is an online wholesale marketplace that uses machine learning to connect independent retailers with brands globally. This Senior Data Scientist role on the Retailer team focuses on developing algorithmic solutions for shipping cost optimization, credit underwriting, and retailer growth strategies.","job_description":{"responsibilities":["Build ML models for accurate shipping cost estimates using live carrier information.","Improve Net terms portfolio by evaluating retailer creditworthiness and optimizing credit limits.","Develop models for retailer growth, including SEO optimization, landing page personalization, and lifetime value prediction.","Collaborate with data scientists, engineers, and product managers to drive marketplace data projects."],"minimum_qualifications":["Advanced degree (MS or PhD) in statistics, economics, econometrics, mathematics, computer science, or operations research.","3+ years of experience productionizing machine learning models using Sklearn, XGBoost, or Deep Learning.","Strong programming skills in Python, Java, Kotlin, or C++.","Knowledge of statistical techniques such as experimentation and causal inference."],"preferred_qualifications":["SQL or other database querying experience."]},"visa_sponsorship":null,"experience_years_min":3,"job_address":null,"job_city":"San Francisco","job_state":"CA","job_country":"US","location_lat":37.7749295,"location_lng":-122.41941550000001,"keywords":["product managers","machine learning","data scientists","experimentation","deep learning","landing pages","data science","landing page","intelligence","Collaborate","performance","advertising","competitive","engineering","operations","enterprise","statistics","predictive","algorithms","processing","ML models","database","Platform","modeling","internal","research","privacy","develop","Growth","global","Python","Kotlin","Square","Google","local","craft","forms","data","Java","SQL","C++","SEO","ML","AI","C+"],"company":{"name":"Faire","logo_url":"https://img.logo.dev/faire.com?token=pk_fWx5G5QrQMm-0Ud8BW3mBg&size=64&format=png","description":"Faire operates an online wholesale marketplace that uses data and machine learning to connect independent retailers with brands globally.","website_url":"https://faire.com","linkedin_url":"https://www.linkedin.com/company/fairewholesale","glassdoor_url":null,"x_url":"https://x.com/faire_wholesale","instagram_url":"https://www.instagram.com/faire_wholesale/","youtube_url":null,"github_url":null,"huggingface_url":null,"tiktok_url":"https://www.tiktok.com/@faire_wholesale","crunchbase_url":"https://www.crunchbase.com/organization/faire","facebook_url":"https://www.facebook.com/FaireWholesale","employee_count_range":"1001-5000","employee_count":null,"founded_year":2017,"headquarters":{"address":"100 Potrero Avenue, San Francisco, CA 94103, United States","city":"San Francisco, CA","country":"US","lat":37.7879363,"lng":-122.4075201},"industry":"ecommerce","company_type":"startup","total_funding_usd":1692000000,"locations":["Chicago, IL","Kitchener-Waterloo, Canada","Kitchener-Waterloo, ON","London, UK","London, United Kingdom","New York City, NY","New York, NY","San Francisco, CA","Toronto, Canada","Toronto, ON"]}}