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AI Audience Segmentation Model Developer

Aaliyah Okafor

Full-time · Job · New_York

About the role

Our personalization platform segments 18 million users across 60 B2C clients — subscription boxes, streaming apps, e-commerce stores. The audience segments drive every downstream decision: which content to show, which discount to offer, which channel to use. When segments are stale or coarse, every personalization downstream suffers. You'll rebuild our segmentation model stack from the ground up. The current system runs K-means on behavioral features with weekly batch updates. We need something more dynamic: online clustering that updates as users behave, hierarchical segments that support both broad and fine-grained targeting, and a segment quality scoring system that tells clients when their audiences have drifted from their original intent. The data science team is seven people. You'll own this project with a junior analyst supporting you. The output isn't just a model — it's an API and UI component that client success teams use to configure and evaluate audiences without writing code.

Responsibilities

  • Redesign the audience segmentation system from batch K-means to dynamic online clustering
  • Build hierarchical segment structures supporting broad and fine-grained targeting
  • Develop segment quality scoring to detect audience drift over time
  • Create APIs that expose segment configuration to client-facing product teams
  • Design evaluation frameworks measuring segment business impact vs. a baseline
  • Collaborate with client success teams to translate business targeting needs into model objectives

Requirements

  • 3+ years in ML or data science with customer segmentation or behavioral analytics experience
  • Strong Python and SQL skills for feature engineering at scale
  • Experience with clustering algorithms and unsupervised learning techniques
  • Familiarity with online or streaming ML for real-time model updates
  • Ability to communicate model design decisions to non-technical stakeholders

Benefits

  • Fully remote with flexible hours
  • Health, dental, and vision insurance
  • 401(k) with 4% match
  • $3,000 annual professional development budget
  • Quarterly performance reviews

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Categories

data science & analytics AI Business, Marketing & Strategy

Skills

python pytorch sql spark pandas

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Level

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Language

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Salary Range

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AI Expertise

data science & analytics AI Business, Marketing & Strategy

Skills

python pytorch sql spark pandas statistics

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