Data Scientist, AI/ML Predictive Maintenance Platform
Summary
Build and deploy AI/ML models for predictive maintenance using IoT sensor data, focusing on anomaly detection and failure prediction with rapid iteration into production.
## Data Scientist, AI/ML Predictive Maintenance PlatformApplylocations:
Singaporetime type:
Full timeposted on:
Posted Yesterdayjob requisition id:
10016034## **JOB DESCRIPTION**We are seeking a skilled and pragmatic Data Scientist to join our team in shaping the next-generation AI/ML-based predictive maintenance platform. You’ll work on applying both classical and Gen AI techniques to real-time IoT signals across diverse physical assets. If you thrive in fast iterations, own your experiments, and believe in getting things to production—not just Jupyter notebooks—this role is
for you.**Key Responsibilities****1. Model Development*** Develop, train, and fine-tune models on time-series sensor data for both anomaly detection and failure prediction across various asset types.* Explore and apply a mix of forecasting, anomaly detection, change point detection, survival analysis, and representation learning techniques, choosing the best fit based on the use case.* Be comfortable applying hybrid approaches (e.g., combining statistical thresholds with ML models, or chaining changepoint detection with LSTM/Transformer predictors) when appropriate.* Iterate quickly and deliver working ML models into dev or production environments every 1–2 week sprint, enabling rapid feedback and continuous improvement.* Balance performance, explainability, compute cost, and deployment constraints in every modeling decision**2. Model Performance Monitoring*** Continuously monitor model performance in production (e.g., accuracy, drift, recall).* Build a retraining and rollback strategy to handle data drift, model drift or edge cases.* Use dashboards or alerts to track live model degradation.* Proactively recommend model retirement or replacement.**3. Team Player*** Clearly explain model behavior (e.g. thresholds, decision boundaries).* Share experiment results, performance comparisons, and trade-offs transparently.* Collaborate with product managers, engineers, and non-technical stakeholders.* Align ML decisions across the team for unified communication.* Follow lean documentation principles: be precise, but cover key code, decisions, and the chosen approach## **JOB REQUIREMENTS**-## **BUSINESS SEGMENT**Connectivity## **PLATFORM**Operating Division### About UsKeppel is a global asset manager and operator headquartered in Singapore. With operations in more than 20 countries worldwide, we provide innovative solutions that address some of the world's most pressing needs across the energy transition, rapid urbanisation, and increasing digitalisation.With sustainability at the core of our strategy, Keppel harnesses the strengths and expertise of our business units to develop, operate and maintain real assets, which provide diverse solutions that are good for the planet, for people and for the Company.Keppel actively seeks out bright and dynamic individuals to join our talent pool. We offer our employees opportunities to grow and shape their careers, across the geographies in which we operate.Be part of our Keppel family today.
Singaporetime type:
Full timeposted on:
Posted Yesterdayjob requisition id:
10016034## **JOB DESCRIPTION**We are seeking a skilled and pragmatic Data Scientist to join our team in shaping the next-generation AI/ML-based predictive maintenance platform. You’ll work on applying both classical and Gen AI techniques to real-time IoT signals across diverse physical assets. If you thrive in fast iterations, own your experiments, and believe in getting things to production—not just Jupyter notebooks—this role is
for you.**Key Responsibilities****1. Model Development*** Develop, train, and fine-tune models on time-series sensor data for both anomaly detection and failure prediction across various asset types.* Explore and apply a mix of forecasting, anomaly detection, change point detection, survival analysis, and representation learning techniques, choosing the best fit based on the use case.* Be comfortable applying hybrid approaches (e.g., combining statistical thresholds with ML models, or chaining changepoint detection with LSTM/Transformer predictors) when appropriate.* Iterate quickly and deliver working ML models into dev or production environments every 1–2 week sprint, enabling rapid feedback and continuous improvement.* Balance performance, explainability, compute cost, and deployment constraints in every modeling decision**2. Model Performance Monitoring*** Continuously monitor model performance in production (e.g., accuracy, drift, recall).* Build a retraining and rollback strategy to handle data drift, model drift or edge cases.* Use dashboards or alerts to track live model degradation.* Proactively recommend model retirement or replacement.**3. Team Player*** Clearly explain model behavior (e.g. thresholds, decision boundaries).* Share experiment results, performance comparisons, and trade-offs transparently.* Collaborate with product managers, engineers, and non-technical stakeholders.* Align ML decisions across the team for unified communication.* Follow lean documentation principles: be precise, but cover key code, decisions, and the chosen approach## **JOB REQUIREMENTS**-## **BUSINESS SEGMENT**Connectivity## **PLATFORM**Operating Division### About UsKeppel is a global asset manager and operator headquartered in Singapore. With operations in more than 20 countries worldwide, we provide innovative solutions that address some of the world's most pressing needs across the energy transition, rapid urbanisation, and increasing digitalisation.With sustainability at the core of our strategy, Keppel harnesses the strengths and expertise of our business units to develop, operate and maintain real assets, which provide diverse solutions that are good for the planet, for people and for the Company.Keppel actively seeks out bright and dynamic individuals to join our talent pool. We offer our employees opportunities to grow and shape their careers, across the geographies in which we operate.Be part of our Keppel family today.