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AI Player Behavior Clustering Analyst

Penelope Moreau

Full-time · Job · New_York

About the role

Sports analytics platforms drown in data — 4,000 data points per NBA game, 1,200 per soccer match, real-time odds from 40 bookmakers. The teams and bettors who win are the ones who find patterns that others miss. Our clustering system identifies player behavioral archetypes that go beyond box-score stats: shot selection tendencies under pressure, defensive positioning habits, fatigue-driven performance decay curves. You'll build the clustering pipeline that processes player tracking data across multiple sports, identifies meaningful behavioral segments, and tracks how players shift between clusters over a season. The clusters feed our prediction models — knowing that a player has transitioned from an "aggressive attacker" to a "conservative playmaker" cluster improves match outcome predictions by 8%. The sports analytics team is five people. You'll work alongside a domain analyst who has 10 years of professional sports analytics experience and can validate whether your statistical clusters map to real tactical patterns that coaches and scouts recognize.

Responsibilities

  • Build player behavior clustering from tracking data across multiple sports
  • Design features capturing shot selection, positioning, and fatigue patterns
  • Track cluster transitions over time and correlate with performance changes
  • Validate statistical clusters against domain expert tactical knowledge
  • Feed cluster assignments into match outcome prediction models
  • Create visualizations that scouts and analysts can interpret

Requirements

  • 3+ years in data science with clustering or behavioral analytics
  • Strong Python, SQL, and scikit-learn skills
  • Experience with time series feature engineering
  • Understanding of unsupervised learning evaluation methods
  • Interest in sports analytics or competitive gaming

Benefits

  • Fully remote with flexible hours
  • Health and dental insurance
  • $2,500 learning budget
  • Access to proprietary sports tracking datasets
  • Quarterly team events

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python sql scikit-learn pandas statistics

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

data science & analytics AI & Machine Learning Engineers

Skills

python sql scikit-learn pandas statistics pytorch

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