Data Scientist - Predictive Maintenance
Core
Develop predictive maintenance algorithms and models to monitor industrial equipment, predict failures, and optimize asset reliability using time-series data and machine learning.
Role type
Senior IC machine-learning engineer (predictive maintenance)
Builds
Scalable, real-time predictive models and diagnostic tools for industrial asset monitoring
Domain
Industrial IoT / Predictive Maintenance / Condition Monitoring
Deliverable
production ML models
Required skills
Machine learning, time-series analysis, anomaly detection, Python, NumPy, pandas, scikit-learn, PyTorch, signal processing, industrial sensor data analysis, experimental design
Preferred skills
Academic research translation, fault diagnosis, prognostics, vibration-based methods, industrial/manufacturing environment experience
Technologies
Python, NumPy, pandas, scikit-learn, PyTorch
Responsibilities
Develop predictive maintenance algorithms for time-series data; Analyze sensor data streams to identify failure patterns; Research and apply state-of-the-art condition monitoring techniques; Collaborate with engineers to improve data pipelines and model accuracy; Build scalable, real-time models for low-latency predictions; Create diagnostic tools for data-driven maintenance decisions; Work with laboratory teams to design experiments and validate models using real machinery; Continuously refine models based on real-world performance and feedback