Data Scientist & AI Engineer

Data Scientist
Remote
August 31, 2026
Full Time
Application ends: November 30, 2026
Apply Now

Job Description

THE ROLE

Working closely with data science teams, technical leaders, business stakeholders and platform partners, you will deliver end-to-end data engineering and MLOps capability to support custom AI solutions across mine operations.Key responsibilities include

  • Design and build robust data feature pipelines to support machine learning models and AI use cases
  • Process large-scale datasets using PySpark and cloud-based object storage to enable data science initiatives
  • Conduct data discovery, dependency mapping and scope definition for AI data migration and platform integration
  • Establish and optimise MLOps lifecycles, including CI/CD pipelines and release processes using Azure DevOps
  • Build custom Docker images and deploy containerised services for machine learning models
  • Audit existing deployments and produce comprehensive technical documentation for previously undocumented solutions
  • Engage with key stakeholders to present model results and data visualisations, and ensure seamless integration with downstream Power BI and Power Apps platforms

THE COMPANY

A leading mining industry organisation is seeking an experienced Data Scientist & AI Engineer to support the delivery of custom AI and machine learning solutions across its operations. Operating within a complex data and analytics environment, this organisation is investing in modern, scalable and well-governed AI capability to support critical operational decision-making and future technology initiatives.SKILLS & EXPERIENCE

  • Extensive background in Data Engineering or Machine Learning Engineering, with deep technical expertise in Azure and Databricks
  • Advanced proficiency in Python and PySpark for complex data processing and writing optimised notebooks
  • Proven experience with MLOps, with a clear understanding of the end-to-end AI/ML lifecycle and model deployment
  • Hands-on experience with containerisation (Docker) and CI/CD release processes via Azure DevOps
  • Familiarity with large-scale object storage, SQL, and streaming data into visualisation tools such as Power BI and Power Apps
  • Strong analytical capability for data discovery, fact-finding and scoping technical requirements
  • Proven consulting capability, with the ability to present complex model results to non-technical stakeholders
  • Official certifications in Microsoft Azure and/or Databricks are highly desirable
  • Previous experience within mining, resources or other large, complex enterprise environments will be highly regarded

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