Senior Applied AI/ML Scientist — Shape Local Retail AI

Faire; San Francisco (CA); Hybrid; USD 211,000 - 290,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Faire, a technology wholesale platform, is seeking a Data Scientist for the Retailer team in San Francisco. You’ll tackle shipping cost optimization, underwriting, and retailer growth, leveraging ML and NLP to improve search, personalization, and value extraction from two-sided marketplace data.

Collaborate with data scientists, engineers, and product managers to drive projects that unlock value from rich data.

Qualifications

• An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.
• 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, or Deep Learning).
• Strong programming skills (Python, Java, Kotlin, C++).
• Knowledge of statistical techniques such as experimentation and causal inference.
• SQL or other database querying experience preferred.
• Willingness to learn new tools and techniques.

Responsibilities

• Shipping cost optimization: Build ML models that provide accurate shipping cost estimates and engineer features to boost performance.
• Underwriting: Evaluate retailers' creditworthiness and dynamically assign credit terms to balance risk and growth.
• Retailer Growth & Lifecycle: Generate landing pages, understand keyword intent with NLP, and predict retailer lifetime value to optimize acquisition spend.

Skills

ML skills

Production ML

Python

Java

Kotlin

C++

Statistics

SQL

Willingness to learn

Education

MS or PhD

Tools

Scikit-learn

XGBoost

Deep Learning

Job description

Faire, a technology wholesale platform, is seeking a Data Scientist for the Retailer team in San Francisco. You’ll tackle shipping cost optimization, underwriting, and retailer growth, leveraging ML and NLP to improve search, personalization, and value extraction from two-sided marketplace data.

Collaborate with data scientists, engineers, and product managers to drive projects that unlock value from rich data.