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AI Player Biometric Performance Tracker

Claire Schneider

Full-time · Job · Los_Angeles

About the role

Sports performance broadcasting is moving from descriptive to analytical: viewers want to know not just what happened but what it means in performance terms. Athlete biometric tracking — heart rate, acceleration, deceleration, distance, sprinting speed — extracted from broadcast camera feeds and wearable sensor streams, combined with contextual game state analysis, lets broadcasters tell the performance story of the match: who's fatiguing, who's operating at their performance ceiling, and which moments of peak physical output changed the game. We serve 8 sports broadcasting organizations and 12 sports league analytics teams. Biometric performance tracking from broadcast feeds is a new capability we're building to complement our existing video analytics. The challenge is multi-modal: biometric data from wearables, pose estimation from video, tracking data from optical player tracking, and game event context all need to be fused into a coherent performance narrative. You'll lead the biometric tracking fusion system: designing the multi-source data integration architecture, building the performance state models that interpret biometric signals in game context, and creating the performance insight generation that turns sensor data into broadcast-ready narrative elements.

Responsibilities

  • Design multi-source biometric fusion architecture integrating wearable sensors, pose estimation, and optical tracking
  • Build performance state models interpreting biometric signals in game context: fatigue onset, peak output windows
  • Implement player comparison analytics benchmarking in-game biometric performance against individual baselines
  • Develop broadcast annotation generation producing performance insight overlays and narrative elements
  • Create injury risk flagging identifying biometric patterns correlating with elevated injury probability
  • Build real-time performance dashboard for coaching staff use during match intervals

Requirements

  • 6+ years in sports analytics, biomedical data science, or computer vision with athlete performance modeling
  • Deep understanding of sports biomechanics, athletic performance metrics, and physiological fatigue indicators
  • Strong Python and computer vision skills with multi-modal sensor fusion experience
  • Experience working with wearable sensor data, optical tracking systems, and broadcast video pipelines
  • Track record building analytics systems adopted by professional sports teams or broadcasters

Benefits

  • Fully remote with occasional travel to sports events for system validation
  • Comprehensive health benefits
  • $4,000 annual professional development budget
  • Equity participation
  • Credit in broadcast productions using your system

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch computer vision sql pandas

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Job Type

Full-time

Level

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Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python pytorch computer vision sql pandas statistics

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