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AI Conveyor Belt Wear Pattern Predictor

Ethan Park

Full-time · Job · Chicago

About the role

Our digital twin platform already models factory layouts and predictive maintenance for major equipment classes, but conveyor systems have been treated as a black box. Unplanned conveyor belt failures cause some of the longest downtime events across our client factories because replacement parts often aren't stocked locally. This role builds a wear pattern prediction model specific to conveyor belts using vibration, load, and maintenance history data, feeding directly into our existing spare parts inventory system.

Responsibilities

  • Build wear pattern prediction models specific to conveyor belt systems
  • Combine vibration, load, and maintenance history data into the model
  • Feed predictions into the existing spare parts inventory planning system
  • Validate predictions against actual failure events across client factories

Requirements

  • 3+ years building predictive maintenance or industrial time-series models
  • Strong Python, SQL, and pandas skills
  • Experience with Power BI or similar reporting tools
  • Comfortable visiting client factories periodically for data validation

Benefits

  • Hybrid schedule with occasional factory site visits
  • Health and dental insurance
  • Equity package
  • Industrial IoT hardware training
  • 401k matching

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Categories

data science & analytics AI & Machine Learning Engineers

Skills

python sql pandas statistics power bi

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Level

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Language

English

Salary Range

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AI Expertise

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Skills

python sql pandas statistics power bi

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