Senior Applied AI/ML Scientist - Brand Growth

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 specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. We are dedicated to building machine learning models that help our customers thrive.

As a Senior Applied AI/ML Scientist on the Brand Growth team, you will own the modeling and measurement for a set of problems that help Faire acquire and grow the brands on our marketplace, which connects hundreds of thousands of independent brands and retailers.

Because our users are businesses, there is a wealth of information about them that ML models can use to personalize their experience, grow their success, and prioritize where we invest. You will work across structured and unstructured data using methods that range from personalization and recommendations to causal inference, lifetime-value modeling, and information extraction.

You will partner closely with product, engineering, marketing, and sales, and you will drive projects end-to-end from framing through production and measurement.

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

What you'll do

• Own applied ML projects end-to-end: framing the problem, building and shipping the model, and measuring impact.
• Optimize marketing and acquisition spend for acquiring new brands through targeting, lookalike audiences, and personalization.
• Predict brand lifetime value to prioritize brand leads for sales and to personalize new-brand onboarding.
• Improve cold-start recommendations and exploration so that new brands find the right retailer audience quickly.
• Identify and enrich brand leads from internal and external data (e.g. retailer search behavior, referrals, and third-party sources) to power prioritization and personalization.
• Use experimentation and causal inference to measure the effectiveness of growth and spend levers.
• Partner across product, engineering, marketing, sales, and analytics to turn models into shipped product and business impact.
• Solve challenging problems related to a two-sided marketplace.

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
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions 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, or related STEM fields.
• Previous experience in marketplace growth, acquisition / paid marketing, LTV modeling, or personalization for a two-sided platform.

Salary Range

San Francisco: the pay range for this role is $211,000 to $290,500 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 uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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.