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Salary: CAD 180,000 - 247,500 / 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 keyword intelligence, smart audience targeting, incrementality and efficiency estimation, and Answer Engine Optimization (AEO).
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 the 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 top-tier investors including Y Combinator, Sequoia Capital, Khosla Ventures, and others. Faire has headquarters in San Francisco and Kitchener-Waterloo, with offices in Toronto, London, and New York.
Hybrid employees work in the office 3 days per week (Tuesdays, Thursdays, and one flex day) with flexibility to work remotely up to 4 weeks per year.
**Requirements:**
- 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
