Senior Data Scientist - Ads Modeling

About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. 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 that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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 is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced data scientists and machine learning engineers are developing solutions related to discovery, ads & monetization, ranking, search, recommendations, logistics, underwriting, and more - all with the goal of helping local retail thrive.

The Data Science team owns a wide variety of algorithms and models that power the marketplace. We care about building machine learning models that help our customers thrive.

As a member of the Data Science team you’ll develop machine learning-powered ads ranking models while contributing and adding impact and personalization to our search and discovery system functions. You’ll determine answers to questions like, how relevant is this ad/product to this retailer and how can we infer that in real-time? Can we create real-time embeddings of users' interests and use them to power rankings? How can we improve the ads purchase flow? What techniques can we use to enable our A/B tests to more quickly converge when dealing with low sample sizes?

Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, Netflix and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there!

What you’ll do

• You’ll build best-in-class models to solve various problems at the intersection of Ads Modeling domain and Search and Recommendation.
• You’ll be able to develop vision and execution plan for the Ads team and actively participate in the long-term roadmap as we monetize the platform.
• Collaborate with Data Scientist and ML Engineers across the Data organization to implement tools for ads experimentation.
• Develop key metrics for ads performance evaluation; design dashboards to track them.

Qualifications

• 3.5 years of industry experience in ads/ads modeling domain (ads ranking, auction design, bidding, targeting, etc.) and using machine learning to solve real-world problems
• Experience with search/query processing for ads product development
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• Lead model development without supervision
• Strong communication skills and the ability to excel in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement innovative algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $192,000 to $264,000 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 and may be modified in the future.

Effective January 2025, Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays. 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. 

Applications for this position will be accepted for a minimum of 30 days from the posting date.

Why you’ll love working at Faire

• We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We