Faire is looking to empower local retail businesses with the tools they need to succeed by leveraging the power of machine learning and data insights to revolutionize the wholesale industry.
Requirements
- Strong machine learning skills and 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
Responsibilities
- Build ML models that provide accurate shipping cost estimates and engineer new features to improve model performance
- Improve Faire’s Net terms portfolio by evaluating creditworthiness of retailers on Faire’s platform using predictive modeling
- Build models to automatically generate landing pages and content to target search engine demand
- Use natural language processing to understand search engine keyword intent and match to relevant internal content
- Build ML models to generate intelligence about retailers to power personalization
- Predict retailer lifetime values to optimize retailer acquisition spend
Other
- An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.
- An excitement and willingness to learn new tools and techniques
- In-office on a hybrid schedule - Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays
- Flexibility to work remotely up to 4 weeks per year
