Data Scientist – Predictive Maintenance & Condition Monitoring

On behalf of one of its clients in Industrial technology solutions, the French Chamber of Commerce in Singapore is seeking an experienced Data Scientist with proven experience in data science and engineering to develop AI/ML solutions for predictive maintenance and condition monitoring of industrial equipment. The ideal candidate will work with high-frequency sensor data, particularly vibration signals, to develop machine learning models that detect anomalies, diagnose faults, estimate remaining useful life (RUL), and improve asset reliability. Responsibilities: • Analyze vibration signals from rotating machinery (e.g., bearings, gearboxes, pumps, and compressors) using industrial sensing solutions. • Perform feature extraction and signal analysis in the time, frequency, and time-frequency domains. • Develop, deploy, and optimize AI/ML models for predictive maintenance, condition monitoring, anomaly detection, failure prediction, and Remaining Useful Life (RUL) estimation. • Evaluate emerging technologies, startups, and foundation model solutions relevant to industrial AI, predictive maintenance, and condition monitoring, assessing their technical capabilities. • Lead and manage vibration-based predictive maintenance projects as the technical focal point, overseeing the full project lifecycle from initiation and deployment to business value realization, in close collaboration with nominated subcontractors and system integrators. Requirements: • Bachelor’s/Master’s/PhD degree in Computer Science, Electrical Engineering, Mechanical Engineering, Mathematics, Statistics, Physics, or a related field from a reputable institution. • Minimum 5 years of hands-on experience in AI/ML algorithm development, deployment, and industrial predictive maintenance applications. • Proven track records of delivering at least two end-to-end project lifecycles, from data acquisition and model development to deployment and operationalization. • Strong practical problem-solving skills with the ability to work independently and drive projects from concept to implementation. • Strong knowledge of data science, machine learning, signal processing, and time-series analytics, with proficiency in Python and related AI frameworks. • Familiarity with vibration analysis, predictive maintenance, and condition monitoring for industrial equipment; knowledge of MIBoC (Mobius Institute Board of Certification) vibration methodologies or certification is a plus. • Experience with cloud platforms (AWS, Azure, GCP) and a self-driven, proactive mindset with the ability to work independently in a fast-paced environment. certification is a plus.