Industrial D&I Data Scientist: ML for Prognostics

SLB; Kuala Lumpur; On-site; MYR 120,000 - 210,000; Full time

Job summary

SLB in Kuala Lumpur seeks a Data Scientist to tackle open-ended data problems and invent new algorithms for industrial diagnostics. The role requires an advanced degree in a quantitative field and 3–12 years of experience in ML, statistics, and data-driven modeling.

You will work on time-series forecasting, anomaly detection, and AI/ML deployment across enterprise-scale systems, leveraging GenAI/LLMs and cloud-enabled data pipelines.

Qualifications

• 3–12 years of experience in data science, ML, or related fields.
• Strong background in statistical analysis and machine learning techniques.
• Ability to formulate and solve industrial data problems using advanced algorithms.

Responsibilities

• Research and assess next-generation technologies for diagnostics and data-driven optimization of complex systems.
• Demonstrate advanced ML knowledge and population-based optimization methods.
• Generate innovative ideas and shape technical projects from concept to deployment.
• Maintain state-of-the-art knowledge and contribute to technical discussions.
• Apply theoretical knowledge to solve industrial problems.
• Process large multivariate data from equipment operations and tests.
• Develop data-driven algorithms for anomaly detection and failure prediction.
• Communicate ideas and results effectively via reports.
• Collaborate with field and product engineers to identify health monitoring parameters.

Skills

Python

ML Ops

DevOps

Version control

Explainable AI

Time-series

Bayesian techniques

NLP-GenAI

Education

Advanced degree in quantitative field

Tools

NumPy

pandas

scikit-learn

Keras

TensorFlow

PyTorch

Job description

SLB in Kuala Lumpur seeks a Data Scientist to tackle open-ended data problems and invent new algorithms for industrial diagnostics. The role requires an advanced degree in a quantitative field and 3–12 years of experience in ML, statistics, and data-driven modeling.

You will work on time-series forecasting, anomaly detection, and AI/ML deployment across enterprise-scale systems, leveraging GenAI/LLMs and cloud-enabled data pipelines.