Staff Applied AI/ML Scientist, Acquisition

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.

We’re looking for a Staff Applied AI/ML Scientist, Acquisition to own data science vision, strategy, and execution for how Faire finds and acquires independent retailers who shop on our marketplace. You will build models that decide where and how much we spend across paid channels, predict the long-term value of prospective retailers, generate landing pages and content, and shape the experience retailers have before they sign up.

Responsibilities:

• Drive AI/ML vision, strategy, and roadmap for Acquisition and Paid Marketing
• Optimize paid marketing spend, bidding, and budget allocation across channels
• Predict retailer lifetime value and use it to power value-based bidding and prioritize acquisition effort
• Design experiments to measure the incremental impact of paid channels and spend levers
• Develop keyword, SEO, and AEO intelligence to identify and prioritize search and content opportunities
• Generate landing pages and content at scale, and measure their impact on acquisition
• Build audience and targeting models for retargeting campaigns
• Manage and mentor Applied AI/ML Scientists and Analytics Engineers, and grow the team through hiring
• Partner closely with marketing, product, engineering, and finance to translate models into measurable growth

Qualifications:

• 5+ years of industry experience using machine learning to solve real-world problems
• Experience with relevant business problems (e-commerce, marketplaces, growth, acquisition, paid marketing, or personalization)
• Experience with relevant technical methods (incrementality measurement, LTV modeling, bidding and budget optimization, recommendations and cold-start, and/or LLMs for production solutions)
• Strong programming skills
• Excitement and willingness to learn new tools and techniques
• Experience as a tech lead, mentoring other scientists or machine learning engineers, and the ability to set team strategy and lead model development without supervision
• Strong communication skills and the ability to work in a highly cross-functional team

Benefits:

• Flexible paid time off, plus company-wide recharge days
• Paid parental leave up to 16 weeks
• Comprehensive health coverage
• Fertility and family-building benefits
• Mental health support and coaching
• Stipends to support professional development, wellness, and work from home needs
• Employer-sponsored retirement plan