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AI Fan Engagement Personalization Engineer

Claire Schneider

Full-time · Job · New_York

About the role

We power the digital experience for 12 professional sports teams — apps, websites, and second-screen activations used by 8 million fans per day during game days. A fan's experience during a live game should feel different depending on whether they're a season ticket holder who watches every play or a casual fan who checks scores during commercial breaks. Right now, they get the same content. You'll build the personalization layer that makes fan experiences context-aware: recommending the right content during key game moments, surfacing merchandise relevant to each fan's history, and adapting the information density based on viewing behavior signals. The content library is large — 40,000 assets across live stats, highlight clips, player profiles, and merchandise — and the recommendation window is often under 30 seconds between significant game events. This is a mid-level engineering role with product impact on a uniquely visible platform. When you improve the personalization, 8 million fans experience the difference.

Responsibilities

  • Build real-time content personalization recommendations for 8M daily active fans
  • Design contextual recommendation models triggered by live game events
  • Implement behavioral feature engineering from app interaction and viewing patterns
  • Create A/B testing frameworks for personalization experiments during live games
  • Monitor recommendation quality metrics: click-through, watch time, conversion
  • Collaborate with content teams to understand asset taxonomy and metadata

Requirements

  • 3+ years in recommendation systems or personalization engineering
  • Experience with real-time or contextual recommendation architectures
  • Strong Python and SQL skills with event-driven data processing experience
  • Familiarity with content-based and collaborative filtering approaches
  • Ability to optimize for multiple engagement metrics simultaneously

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • 401(k) with match
  • Complimentary tickets to client team home games
  • $2,500 annual professional development fund

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Categories

AI Business, Marketing & Strategy data science & analytics

Skills

python pytorch sql spark pandas

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

AI Business, Marketing & Strategy data science & analytics

Skills

python pytorch sql spark pandas statistics

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