Build industrial data science solutions using sensor, PLC, historian, and MES data. Develop predictive maintenance, anomaly detection, remaining-useful-life, quality, and yield models. Deploy models to edge or cloud, create operator dashboards, and collaborate with plant engineers to refine insights and improve factory processes.
Industrial Data Scientist
Turn raw machine telemetry into predictive maintenance and process insights that help the factory self-correct.
What you'll do
- Clean, contextualize and model time-series data from sensors, PLCs, historians and MES
- Build predictive maintenance, anomaly detection and remaining-useful-life models
- Develop multi-sensor correlation models for quality and yield
- Deploy models to edge or cloud and build operator-facing dashboards
- Walk plant engineers through results on the floor and refine models with their input
Requirements
- 4+ years in data science, with industrial or manufacturing data experience
- Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL
- Experience with time-series and signal data (vibration, temperature, current)
- Familiarity with historians such as AVEVA PI or Canary
Nice to have: Databricks, Azure/AWS ML services, MLOps, reliability engineering knowledge, Power BI or Grafana.
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