Description
As a Staff Applied Scientist on the Discovery team, you'll own how Faire measures and optimizes the long-term value of a discovery impression , one of the highest-leverage open problems on our marketplace.
You'll build the LTV framework, design experiments to validate it, and turn the result into a shared signal that all discovery algorithms can act on.
Responsibilities:
- Own how we measure and optimize the long-term value of a discovery impression , how it contributes to the discovery of new brands retailers might love, and how it strengthens existing promising relationships so they compound.
- Create the initial LTV framework: form and prioritize hypotheses about what drives long-term relationship value and the key short- vs. long-term tradeoffs, with assumptions made explicit and testable, and lay out the experimentation roadmap to validate and refine it.
- Lead the implementation of v0 of the LTV model into a long-running ranking experiment, setting north star metrics as well as guardrails to maximize organizational learning, with a defined readout cadence and course-correction plan.
- Deliver the long-term surrogate metric , a near-term readout predictive of long-term value , accounting for confounding factors and inherent uncertainties in measurement and marketplace dynamics.
- Own the LTV model tech stack and operating standards, continuously improving the capabilities and accuracy of the model as it becomes consumable across search, reorder, and ads.
Requirements:
- 5+ years applying ML and statistical modeling to real business problems, shipping to production.
- Deep causal inference expertise , quasi-experimental methods, rigorous confounder control, and healthy skepticism of analytical results.
- Strong experimentation design skills, especially long-horizon experiments , surrogate/proxy metrics and variance reduction for sparse, delayed outcomes.
- Baseline knowledge of search and recommendation systems on e-commerce or marketplace platforms.
- Strong statistical analysis and data engineering skills , SQL/ETL and data transformation at scale.
- An excitement and willingness to learn new tools and techniques.
- Excellent communication skills and the ability to work in a highly cross-functional team.
Benefits:
- Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.