# Senior Applied AI/ML Scientist - Retailer

**Company**: Faire
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $211,000 to $290,500 per year
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/faire/jobs/7953217002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_6ce118ef-ff0

## Description

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe.

As a Senior Applied AI/ML Scientist on the Retailer team, you'll tackle a diverse set of challenges, such as optimizing logistics and freight costs and calculating optimal credit limits. You'll also contribute to growing Faire's retailer base by enhancing Search Engine Optimization, personalizing landing pages for new retailers, and predicting retailer lifetime value.

Responsibilities:

- Shipping cost optimization: Build ML models that provide accurate shipping cost estimates. Engineer new features to improve model performance. These models may use live carrier information and be both performant and explainable.

- Underwriting: Improve Faire's Net terms portfolio by evaluating creditworthiness of retailers on Faire's platform. Use predictive modeling to dynamically assign credit terms limits that minimize default risk and maximize growth.

- Retailer Growth & Lifecycle: 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.

Qualifications:

- An advanced degree (MS or PhD) in a relevant discipline such as statistics, economics, econometrics, mathematics, computer science, operations research, etc.

- 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

Benefits:

- Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.

- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.

- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.

- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.

- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.

## Skills

### Required
- Machine Learning
- Python
- Java
- Kotlin
- C++
- SQL
- Statistics
- Econometrics
- Mathematics
- Computer Science

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/faire/jobs/7953217002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)