We are looking for a talented and motivated Data Scientist to develop condition monitoring models to power asset management solutions for customers and dealers. You will use machine learning, deep learning, and statistics-based/physics-based analytics techniques on time-series sensor data, machine fault codes, inspections and analysis records, and other datasets to identify health anomalies, predict equipment failure modes, estimate remaining useful life, and build equipment risk models. Excellent python coding skills are paramount, but familiarity with modeling and analysis of heavy equipment engineering systems is a strong plus. Visa sponsorship is available for eligible applicants.
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