Exploration and Mining Artificial Intelligence is essential to improving resource discovery, orebody understanding, safety, planning, productivity, efficiency, and sustainability across Maaden s mining operations.
As Manager, Exploration & Mining Artificial Intelligence, you lead the identification, development, deployment, and adoption of AI solutions across exploration, geology, resource modeling, mine planning, drilling and blasting, material movement, fleet optimization, production, and mine safety. You translate operational challenges into scalable AI solutions and work with exploration, mining operations, technical services, engineering, OT, IT, Digital, and Enterprise AI teams to deliver measurable and sustainable value.
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Develop and maintain a prioritized portfolio of Exploration & Mining AI use cases aligned with business strategy, site priorities, and operational performance targets.
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Assess opportunities based on business value, technical feasibility, data readiness, scalability, operational risk, and adoption requirements.
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Define clear use-case objectives, delivery roadmaps, resource requirements, benefits, and success measures.
Develop and Deploy Exploration & Mining AI Solutions
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Lead the design, development, testing, deployment, and continuous improvement of AI, machine learning, optimization, computer vision, and geospatial analytics solutions for exploration and mining.
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Enable applications such as exploration targeting, geological interpretation, resource estimation support, mine planning optimization, drilling and blasting optimization, fleet productivity, ore tracking, and real-time decision support.
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Ensure solutions are production-ready, scalable, maintainable, explainable, and aligned with operational and technical requirements.
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Improve Exploration and Mining Performance
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Partner with exploration, geology, mine planning, technical services, mining operations, maintenance, and safety teams to identify and solve high-value operational challenges.
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Apply predictive and prescriptive analytics to improve discovery targeting, orebody understanding, plan compliance, equipment utilization, cycle times, material movement, productivity, and cost performance.
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Support hazard detection, fatigue and proximity analytics, equipment health insights, and risk-informed decision-making for safer and more reliable mining operations.
Integrate AI into Mining Environments
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Coordinate integration of AI solutions with geoscience platforms, mine planning systems, fleet management systems, operational technology, historians, asset platforms, enterprise applications, and digital twins.
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Work with Enterprise AI and AI & ML Ops teams to use approved platforms, reusable components, deployment pipelines, monitoring capabilities, and model lifecycle standards.
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Ensure deployed models are monitored for performance, reliability, drift, availability, and continued business value.
Drive Adoption and Value Realization
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Embed AI outputs into exploration workflows, technical services processes, dispatch and operational practices, planning cycles, and management decision-making.
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Lead user engagement, change management, training, and knowledge transfer to support effective adoption and sustainable operational ownership.
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Track realized benefits and report performance against safety, discovery, planning, production, productivity, reliability, cost, and sustainability measures.
Lead Team and Capability Development
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Lead and develop a multidisciplinary team combining AI, data science, geoscience, mining engineering, and operational expertise.
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Set clear priorities, delivery standards, performance expectations, and development plans for team members.
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Build capability through coaching, communities of practice, external partnerships, and structured knowledge transfer.
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Ensure Governance, Safety, and Compliance
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Ensure solutions comply with safety, cybersecurity, data governance, model governance, responsible AI, quality, and operational risk requirements.
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Manage activities within approved scope, budget, schedule, quality, and performance expectations.
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Maintain accurate technical documentation, portfolio reporting, benefit tracking, and stakeholder communication.
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A focused Exploration & Mining AI portfolio aligned with site priorities and measurable business value.
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Improved exploration targeting, orebody understanding, safety, plan quality, production, equipment utilization, and mining productivity.
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Reduced operational variability, cycle time losses, unplanned downtime, safety exposure, and manual decision-making.
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Production-grade AI solutions adopted and sustained within exploration and mining operations.
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Reliable model performance supported by effective monitoring, governance, and operational ownership.
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Strong collaboration across exploration, geology, technical services, mining operations, maintenance, safety, OT, IT, Digital, and Enterprise AI.
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A capable and engaged team with strong AI, geoscience, and mining expertise.
Bachelor s degree in Artificial Intelligence, Data Science, Computer Science, Mining Engineering, Geological Engineering, Geology, Geomatics, Industrial Engineering, or a related discipline. A Master s degree is preferred.
Bachelor s degree in Artificial Intelligence, Data Science, Computer Science, Mining Engineering, Geological Engineering, Geology, Geomatics, Industrial Engineering, or a related discipline. A Master s degree is preferred.
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Exploration & Mining AI strategy and portfolio management
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Machine learning, optimization, computer vision, geospatial analytics, and time-series analytics
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Data Science, Artificial intelligence, machine learning, Generative AI (GenAI), optimization, computer vision, Natural Language Processing (NLP), Large Language Models (LLMs) and Agentic AI.
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Exploration, geology, resource modeling, mine planning, and mining operations
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Drilling and blasting, fleet optimization, material movement, productivity, and mine safety
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Predictive maintenance, equipment health, condition monitoring, and asset reliability
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Geoscience platforms, mine planning systems, fleet management systems, operational technology, and digital twins
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MLOps, model monitoring, lifecycle management, and production deployment
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Responsible AI, cybersecurity, data governance, and operational risk
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Business value realization, benefits tracking, and performance reporting
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Team leadership, stakeholder management, change management, and communication