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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers and products. The company uses machine learning and data insights to help local retailers compete against large e-commerce and retail giants.
You will join the Retailer Growth Data team, focusing on paid marketing and top-of-funnel acquisition channels. Your role is to develop AI/ML systems that activate new retailers and increase their engagement on the platform. The team works on a wide range of ML opportunities including paid marketing optimization, bidding optimization, search keywords intelligence, smart audience targeting, incrementality and efficiency estimation, and Answer Engine Optimization (AEO) using LLMs to create programmatic content at scale.
Key responsibilities include:
- Drive data science vision, strategy, and execution within Retailer Growth using AI/ML solutions
- Work with cross-functional stakeholders to develop end-to-end product solutions
- Extract deep behavioral insights using AI to automate AEO content creation and personalize user landing experiences
- Optimize marketing capital allocation through sophisticated targeting and bidding optimization strategies
- Implement rigorous experimentation and causal inference frameworks to quantify impact of growth levers
- Engineer scalable solutions for complex challenges inherent to two-sided marketplace dynamics
Faire's Applied AI/ML team includes experienced scientists from Uber, Airbnb, Square, Facebook, and Pinterest. The company was founded in 2017 by early product and engineering leads from Square and is backed by Y Combinator, Lightspeed, Forerunner, Khosla, Sequoia, Founders Fund, and DST Global. Headquarters are in San Francisco with offices in Kitchener-Waterloo, Toronto, London, and New York.
Hybrid employees work in office 3 days per week (Tuesdays, Thursdays, and one flex day) with flexibility to work remotely up to 4 weeks per year.
QUALIFICATIONS:
- 3+ years of industry experience using machine learning to solve real-world problems
- Experience with relevant business problems (e-commerce)
- Experience with relevant technical methods (LTV modeling, NLP, LLMs, causal ML, bidding optimization)
- Strong programming skills
- Ability to design and implement ML solutions without supervision
- Strong communication skills and ability to work in highly cross-functional teams
- Excitement and willingness to learn new tools and techniques
GREAT TO HAVES:
- Master's or PhD in Computer Science, Statistics, or related STEM fields
- Previous experience in paid marketing and/or growth teams focusing on SEO and AEO optimization
- Previous experience with LLMs and programmatic content generation
