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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with brands and products. The company uses machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete effectively.
As a Senior Applied AI/ML Scientist on the Brand Growth team, you will own end-to-end modeling and measurement for problems that help Faire acquire and grow brands on its two-sided marketplace. You will work with structured and unstructured data using methods including personalization, recommendations, causal inference, lifetime-value modeling, and information extraction.
Key responsibilities include:
- Own applied ML projects end-to-end: problem framing, model building and shipping, and impact measurement
- 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 personalize new-brand onboarding
- Improve cold-start recommendations and exploration so new brands find the right retailer audience quickly
- Identify and enrich brand leads from internal and external data (retailer search behavior, referrals, third-party sources) to power prioritization and personalization
- Use experimentation and causal inference to measure 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 two-sided marketplace dynamics
You will partner closely with product, engineering, marketing, and sales teams. The team includes experienced Applied AI/ML Scientists from Uber, Airbnb, Square, Facebook, and Pinterest.
Workplace: Hybrid with 3 days per week in office (Tuesdays, Thursdays, and one flex day), with flexibility to work remotely up to 4 weeks per year.
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
- Excitement and willingness to learn new tools and techniques
- Ability to design and implement ML solutions without supervision
- Strong communication skills and ability to work in highly cross-functional teams
GREAT TO HAVES:
- Master's or PhD in Computer Science, Statistics, or related STEM fields (highly recommended)
- Previous experience in marketplace growth, acquisition/paid marketing, LTV modeling, or personalization for a two-sided platform
