AI/ML Data Scientist – Real-Time Predictive Maintenance

Keppel Data Centres

Singapore

Vor Ort

SGD 90.000 - 150.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

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Zusammenfassung

Keppel Data Centres in Singapore seeks a skilled Data Scientist to help shape the next-generation AI/ML-based predictive maintenance platform. You will apply classical and Gen AI techniques to real-time IoT signals across diverse assets, delivering production-ready models with rapid iterations.

You will own experiments, collaborate with product managers and engineers, and balance accuracy with deployment cost and explainability while building monitoring and retraining strategies.

Aufgaben

  • Model Development for time-series sensor data across assets.
  • Train and fine-tune models for anomaly detection and failure prediction.
  • Explore forecasting, anomaly, change point, survival analysis, and representation learning techniques.
  • Apply hybrid approaches combining thresholds with ML models.
  • Deliver working models into dev/production in 1–2 week sprints.
  • Monitor model performance, drift, and recall in production.
  • Plan retraining and rollback strategies for data/model drift.
  • Use dashboards/alerts to track live model health.
  • Collaborate with product managers, engineers, and stakeholders.

Kenntnisse

Model Development
Time-series modeling
Anomaly detection
Forecasting
Change point detection
Survival analysis
Representation learning
LSTM/Transformer
MLOps
Experimentation

Jobbeschreibung

Keppel Data Centres in Singapore seeks a skilled Data Scientist to help shape the next-generation AI/ML-based predictive maintenance platform. You will apply classical and Gen AI techniques to real-time IoT signals across diverse assets, delivering production-ready models with rapid iterations.

You will own experiments, collaborate with product managers and engineers, and balance accuracy with deployment cost and explainability while building monitoring and retraining strategies.

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