Data Scientist – Industrial Machine Learning

About the role

The Data Scientist will design, develop, and deploy advanced machine‑learning solutions for industrial applications such as reliability monitoring, predictive maintenance, and production optimisation. The role works within complex Oil & Gas or Manufacturing environments and requires close collaboration with engineers, subject‑matter experts, and business stakeholders.

Key responsibilities

• Design, develop and operationalise supervised and unsupervised ML models for reliability and predictive‑maintenance use cases.
• Build scalable, production‑grade solutions using distributed computing frameworks (e.g., MapReduce, streaming technologies) and implement MLOps practices including CI/CD pipelines, model versioning and monitoring.
• Translate operational requirements into analytical solutions, lead end‑to‑end data‑science projects from problem definition through deployment and performance drift management.

Required profile

• Minimum 10 years of hands‑on experience designing, deploying and operating ML algorithms for industrial use cases.
• Proven domain expertise in Oil & Gas or Manufacturing environments, with strong understanding of asset performance and process optimisation.
• MS degree in Computer Science, Engineering, Statistics or a related quantitative field.

Required skills

• Python, R, JavaScript (experience with Java or Scala is a plus).
• Mathematical foundations in linear algebra, calculus, probability and statistics.
• Experience with distributed computing (MapReduce, streaming frameworks) and MLOps tools (CI/CD, containerisation, automated testing).