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On-site
Experience
Some experience
About the role
A Data Scientist is needed to create and run machine learning solutions that predict failures and give early warnings for data centre and industrial equipment. The work centres on spotting degradation, forecasting asset health, finding anomalies and estimating how long until failure using sensor readings. It suits someone with solid experimentation habits who can validate models in real operating conditions and handle situations where failures are rarely seen.
What you'll do
Build and validate models from operational sensor data for failure prediction, monitoring degradation of mechanical and electrical assets, early-warning detection, remaining useful life estimation and time-to-threshold forecasting.
Data Scientist, AI/ML Predictive Maintenance Platform job at Keppel, Singapore | WorkJio
Apply and compare survival analysis, time-series forecasting, anomaly detection, change-point detection and representation learning.
Choose modelling approaches based on measurable performance criteria and documented experiment results.
Balance detection performance, false-positive rates, explainability and production deployment needs.
Develop strategies for settings where failure events are absent.
Handle limited labelled failures, class imbalance, weak supervision, proxy labels, transfer learning and sourcing failure data.
Set up validation methods that measure model effectiveness accurately despite few failure examples.
Form hypotheses and design experiments to evaluate competing approaches.
Define baselines, assess alternatives, measure improvements with objective metrics and document findings and limitations.
Justify model selection with evidence rather than preference.
Deploy models into development and production environments.
Monitor precision, recall, drift and data quality.
Establish retraining, rollback and retirement criteria for production models.
Investigate performance degradation and carry out corrective actions.
Work with product managers, software engineers, platform engineers and subject matter experts in the data centre domain with mechanical and electrical engineering knowledge.
Translate operational problems into machine learning problems.
Bring domain expertise into model development, validation and alert interpretation.
Good to know
Based in Singapore.
Full time role.
Requirements
Bachelor's or Master's degree in Engineering, Computer Science, Data Science or a related field
AI/ML specialisation preferred
Mechanical engineering background or strong exposure to mechanical/industrial systems is an advantage
4–7 years of relevant data science or applied machine learning experience
Experience in a large software development organisation or an end-user engineering/industrial environment
At least 2–3 years hands-on building failure prediction, anomaly detection, condition monitoring or predictive maintenance models
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