Senior Data Scientist - Retailer

About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.

As a Data Scientist on the Retailer team, you will work on solving shipping cost problems by leveraging machine learning models, engineering and analysis skills. You will drive continuous improvement of Tier 3 solutions and streamline inputs for Tiers 1 and 2 (based on brand inputs). You will help drive the adoption of the Ship-with-Faire (SWF) program among brands and optimize the SWF program economics.

Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there! 

What you’ll do 

• 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.
• Develop an off-line calculator that can be called as an API for all tier solutions using product weights and dimensions data provided by the brands
• Maximize customer retention while keeping contribution profits in check
• Develop an in-house utility that can expose information about the shipping cost predictions, making model debugging more efficient. This tool should also allow non-technical members to communicate findings with our brands. 
• Tackle complex issues inherent in managing a two-sided marketplace. Your ability to identify and address these challenges will be critical to our continued growth and success.

Qualifications

• Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, Predictive Modeling, 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
• An excitement and willingness to learn new tools and techniques

Salary Range

California / New York: the pay range for this role is $173,000 - $238,000 per year. 

Colorado / Washington / New Jersey: the pay range for this role is $156,000 - $214,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. 

Faire’s flexible work model aims to meet the needs of our diverse employee community by making work more flexible, connected, and inclusive. Depending on the role and needs of the team, Faire employees have the flexibility to choose how they work–whether that’s mainly in the office, remotely, or a mix of both. 

Roles that list only a country in the location are eligible for fully remote work in that country or in- office work at a Faire office in that country, provided employees are located in the registered country/province/state. Roles with only a city location are eligible for in-office or hybrid office work i