Staff Applied AI/ML Scientist, Acquisition San Francisco, CA

Faire Wholesale Inc.; San Francisco (CA); Hybrid; USD 247,000 - 339,000; Full time

Benefits offered by this job

Equity

Benefits

Hybrid work

Job summary

Faire Wholesale Inc. in San Francisco seeks a Staff Applied AI/ML Scientist to lead data science for Acquisition and paid marketing. You will shape strategy, mentor a small team, and build models for spend optimization and retailer LTV in collaboration with product, engineering, and marketing.

Lead AI/ML roadmap, design experiments, and translate models into measurable growth. This role combines hands-on modeling with leadership across cross-functional teams.

Qualifications

• 5+ years of industry experience with ML in real-world problems.
• Experience shaping strategy as tech lead and mentoring scientists.
• Strong cross-functional collaboration and communication.

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 to power bidding and acquisition focus.
• Design experiments to measure incremental impact and guide investments.
• Develop SEO/AI insights to identify high-value retailers and opportunities.
• Generate content and landing pages at scale; measure impact on acquisition.
• Build audience models for retargeting campaigns and growth.
• Manage and mentor Applied AI/ML Scientists and Analytics Engineers.

Skills

ML systems

Tech lead

Cross-functional teams

Communication skills

Experiment design

Budget optimization

Education

Master's or PhD in CS/Stats/Economics

Tools

LLMs

Deep learning

Job description

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. 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 businesses can grow and local communities can thrive.

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 Applied AI/ML Scientists specialise in developing algorithmic solutions for recommender systems, spend optimization, lifetime value (LTV) predictions, and much more. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

At Faire, the Data 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 the tech lead for Acquisition, you will own data science vision, strategy, and execution for how Faire finds and acquires the independent retailers who shop on our marketplace. You will build the models that decide where and how much we spend across paid channels, predict the long-term value of prospective retailers, generate the landing pages and content that bring them to Faire, and shape the experience retailers have before they sign up. You will lead a small team of scientists and analytics engineers and act as a pod lead alongside product, engineering, and marketing partners.

Our team already includes experienced Data Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for Applied AI/ML Scientists, and you will help take us there!

What you’ll do

• Drive AI/ML vision, strategy, and roadmap for Acquisition and Paid Marketing, and act as a pod lead across cross-functional workstreams.
• Optimize paid marketing spend, bidding, and budget allocation across channels such as search, social, and Performance Max.
• Predict retailer lifetime value and use it to power value-based bidding and to prioritize acquisition effort.
• Design experiments to measure the incremental impact of paid channels and spend levers, and turn the results into investment decisions.
• Develop keyword, SEO, and AEO intelligence that identifies and prioritizes the search and content opportunities most likely to bring high-value retailers to Faire.
• Generate landing pages and content at scale, and measure their impact on acquisition.
• Build audience and targeting models for retargeting campaigns.
• Manage and mentorApplied 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).
• An 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.

Great to Haves:

• Highly recommended: Master's or PhD in Computer Science, Statistics, Economics, or related STEM fields.
• Experience as a tech lead manager or people manager of applied ML / data science teams.
• Previous experience in performance / paid marketing, marketing-mix or media-mix modeling, bidding systems, incentive optimization, or growth for a two-sided platform.
• Previous experience with deep learning or language models.

Salary Range

San Francisco: the pay range for this role is $246,500 to $339,000 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.

Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.

Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog .

Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form ( https://bit.ly/faire-form)