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AI Cold Chain Temperature Anomaly Detector

Halvex Data

Remote · $60k – $80k / year · Full-time · Posted 4 months ago

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About the role

A refrigerated truck carrying $400,000 of pharmaceutical products experiences a compressor failure at 2 AM. The temperature creeps up 3 degrees over 6 hours. By morning, the products may be compromised — but without a real-time anomaly detection system, nobody knows until the driver opens the back at delivery. The cargo gets rejected. The loss is total. We build supply chain intelligence for cold chain logistics. Our temperature monitoring platform covers 14,000 active shipments at any time across pharmaceutical, food, and specialty chemical clients. The anomaly detection layer needs to distinguish a genuine temperature excursion from a normal door-open event, sensor calibration drift, or expected variation during loading and unloading. As a junior engineer, you will work on the anomaly detection features: building the baseline models for normal temperature patterns per product and route type, implementing the alert scoring that distinguishes severe excursions from false alarms, and maintaining the evaluation pipeline.

Fully remote.

Responsibilities

  • Build baseline temperature profile models per product category and route type
  • Implement anomaly scoring that distinguishes excursions from normal events
  • Maintain model evaluation pipeline tracking false positive and false negative rates
  • Build data pipelines ingesting IoT sensor streams from temperature loggers
  • Create alert dashboards for logistics operations teams
  • Document model behavior and thresholds for client compliance reporting

Requirements

  • 1+ year of Python and data analysis experience
  • Basic understanding of time series data and anomaly detection concepts
  • SQL proficiency for data extraction and analysis
  • Interest in IoT, logistics, or food/pharma supply chain domains
  • Systematic debugging approach with strong documentation habits

Benefits

  • Fully remote
  • Health and dental
  • $1,500 learning stipend
  • Mentorship from senior data scientist
  • Growth path to mid-level in 18 months

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