Operations Intelligence Engineer / Optimization Engineer

SUMMARY:

POSITION INFO:

Required Skills & Competencies

Analytical Thinking

• Strong ability to interpret complex operational datasets
• Comfortable working with incomplete or imperfect data

Cross-Disciplinary Engineering Mindset

• Ability to work across multiple engineering domains
• Curious and adaptable approach to learning

Communication & Advisory Skills

• Ability to clearly communicate technical insights
• Capable of translating analysis into practical recommendations

Problem Solving

• Strong structured thinking and root-cause analysis capability
• Ability to identify issues and propose actionable improvements

Technical Tools (Beneficial)

• Excel, Python, Power BI or similar
• Industrial data systems / historians
• Mining fleet management systems
• Production or maintenance reporting systems

Preferred Background

• Mining Engineering
• Metallurgical Engineering
• Mechanical Engineering
• Industrial Engineering
• Chemical Engineering
• Systems or Process Engineering

Key Responsibilities:

• Conduct operational data analysis
• Utilize industrial data systems and sources
• Advanced Excel skills for data modelling and analysis
• Develop data visualizations and dashboards using Power BI / Tableau
• Experience with Python or similar for data manipulation and analysis
• Analyze performance metrics and KPIs
• Interpret engineering data and understand processes and systems
• Apply root cause and performance analysis techniques
• Integrate and synthesize data for operational purposes
• Exposure to digital and industrial technologies, with IoT knowledge being advantageous
• Develop reporting and dashboard solutions
  
  

  Data Analysis & Operational Insight

  • Analyse operational datasets from mining operations, processing plants, and equipment systems
  • Interpret production, process, and maintenance data to identify inefficiencies and improvement opportunities
  • Develop insights from plant historians, fleet management systems, production reports, and maintenance records
  • Identify trends related to throughput, recovery, availability, downtime, and equipment performance

  Engineering Interpretation

  • Translate operational data into engineering insights and recommendations
  • Review technical reports and extract key implications for operational improvement
  • Assist stakeholders in understanding drivers behind performance variability and production losses

  Advisory & Stakeholder Support

  • Provide advisory support based on analysis findings
  • Develop recommendations to improve plant performance, mining productivity, and equipment reliability
  • Participate in workshops to review operational performance and improvement initiatives

  Performance & Optimization Reporting

  • Produce clear, concise analytical reports
  • Support development of performance dashboards and reporting tools
  • Assist in tracking and measuring improvement initiatives

  Cross-Disciplinary Analysis

  • Work across multiple domains, including:
    • Mining production
    • Mineral processing
    • Equipment reliability and maintenance
    • Fleet and operational performance
  • Integrate insights across systems to form a holistic view of operations