Data Scientist – Predictive Maintenance & Condition Monitoring

Roles & Responsibilities

Our client is a fast-growing technology company delivering integrated hardware and analytics solutions that help industrial businesses minimize downtime, strengthen reliability, and get more out of their maintenance and operations. As they scale across the region, they are looking for an self-driven and proactive mindset professional to join their Singapore team as:

Data Scientist – Predictive Maintenance & Condition Monitoring

Mission:

We are 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. You 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.

The ideal candidate combines strong data science expertise with knowledge of vibration signal processing and industrial rotating machinery.

Responsibilities:

• Analyze vibration signals from rotating machinery (e.g., bearings, gearboxes, pumps, and compressors) using industrial sensing solutions such as smart data loggers and other condition monitoring systems.

• 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 record 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) with the ability to work independently in a fast-paced environment.

EA Personnel Registration No: R1106329

EA License No: 12C6254

Tell employers what skills you have

Machine Learning
AWS
Physics
Vibration
Mathematics
Google Cloud Platform
Azure Cloud Services
Computer Science
AI Models
Vibration Analysis
Anomaly Detection
Reliability Improvement
Data Science
Electrical Engineering
Mechanical Engineering