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Fabric Inc

Senior Data Scientist, AI Search / AEO Research

Posted 4 Days Ago
Remote
Hiring Remotely in United States
136K-182K Annually
Senior level
Remote
Hiring Remotely in United States
136K-182K Annually
Senior level
Lead research defining fabric's AI shopping roadmap: design and run quantitative studies, build models and benchmarks for AI search (AEO/GEO), run experiments, translate findings into customer-facing insights, and publish research to influence product and go-to-market strategy.
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Who we are: 

Come build the future of commerce with us at fabric. We're building the agentic commerce infrastructure that helps merchants grow, sell, and operate in today's AI-powered shopping experience. Backed by top-tier investors and led by industry and AI veterans, our team is building foundational technology at the intersection of AI, commerce, and great user experience.

Where we hire:  We are both a remote-first and hybrid employer (depending on your role and location). We focus on building our team in the following geographic locations depending on the role.


United States - We're limited to hiring in the following states:

California, Colorado, Georgia, Massachusetts, Minnesota, New Hampshire
Washington

Canada - We're limited to hiring in the following provinces:

Ontario & British Colombia


Your next career:
Shopping is moving from search boxes to answer engines. Shoppers now ask ChatGPT, Perplexity, Gemini, and AI Overviews what to buy — and brands win or lose on whether AI represents their products accurately. This is a wide-open field with no established playbook, and fabric is defining it.

You'll own the research that helps define our AI Shopping roadmap. That means helping shape how we measure a brand's AI Shopping capability and how we optimize for the best outcomes. Your work becomes the research behind fabric's roadmap and the credibility behind our thought leadership.

This is a hybrid role by design — part researcher, part PM, part evangelist, part customer-facing. You'll design the studies, build the models, publish the findings, and sit with customers to show them what the data means for their business.

What you bring to the table:

  • A demonstrated point of view on AI search (AEO/GEO). Whether you've worked hands-on with answer engine / generative engine optimization or studied AI search and digital markets rigorously, you can show what you've learned about how AI search actually behaves — from evidence, not just opinion.
  • A rigorous quantitative foundation. Strong data science, statistical, and causal-inference / econometric skills, with fluency in Python, SQL, or similar. You can frame a question, design the analysis, build the model, and defend the methodology.
  • Original research experience. You've run benchmarks, market studies, or performance studies — designing the question and the method, not just running standard reports.
  • An SEO / search discovery background. You understand discovery from the inside and have grown into rigorous, data-driven measurement of it.
  • Experimentation chops. You've designed and run A/B tests or similar to validate an idea and separate signal from noise.
  • Storytelling with data. You can turn raw numbers into a clear narrative and a defensible point of view, and explain complex findings to non-technical audiences.
  • Comfort with ambiguity. You can help build a measurement function from scratch, not just execute one someone else designed.
  • Deep curiosity about commerce. Genuine interest in e-commerce, marketing, and analytics — you want to understand why shoppers and algorithms behave the way they do.

Nice to have

  • External recognition for your research — press, whitepapers, published benchmarks, or conference talks.
  • Customer-facing or consulting experience — you're comfortable presenting findings and recommendations directly to customers.
  • Familiarity with the AEO/GEO tooling landscape and how brands currently try to measure AI visibility.
  • Experience at an e-commerce, martech, or search company or working closely with retail brands and their product data.
  • An advanced degree or academic research background in economics, digital markets, computational social science, or a related quantitative field.

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