Manager, Exploration & Mining Artificial Intelligence

Role purpose

Portfolio and solution delivery

• Prioritize use cases by business value, feasibility, data readiness, scalability, risk, and adoption needs; define roadmaps, resources, benefits, and success measures.
• Develop and deploy AI, machine learning, optimization, computer vision, and geospatial analytics solutions.
• Support exploration targeting, geological interpretation, resource estimation, mine planning, drilling and blasting, fleet productivity, ore tracking, and real-time decisions.

Operational integration and adoption

• Work with exploration, geology, technical services, mining operations, maintenance, and safety teams to address operational challenges.
• Integrate solutions with geoscience, mine planning, fleet, OT, asset, enterprise, and digital twin systems; coordinate with AI and MLOps teams.
• Monitor models for performance, reliability, drift, availability, and business value; embed outputs into workflows and lead adoption, training, and knowledge transfer.

Leadership and governance

• Lead a multidisciplinary AI, data science, geoscience, mining engineering, and operations team; set priorities, standards, and development plans.
• Ensure safety, cybersecurity, data and model governance, responsible AI, quality, and operational risk compliance.
• Manage approved scope, budget, schedule, quality, reporting, documentation, and benefit tracking.

Minimum qualifications and experience

• Bachelor’s degree in AI, Data Science, Computer Science, mining or geological engineering, geology, geomatics, industrial engineering, or a related discipline; a master’s degree is preferred.
• 10+ years of relevant experience, including 5+ years in AI, advanced analytics, geospatial analytics, mining optimization, automation, or digital transformation.
• Experience leading multidisciplinary teams and delivering AI or advanced analytics in exploration, mining, or operational environments.
• Experience progressing solutions from use-case definition through production deployment, adoption, and value realization; asset-intensive industry experience is ideal.

Skills and domains

• Exploration and mining AI; machine learning, optimization, computer vision, geospatial and time-series analytics, data science, GenAI, NLP, LLMs, and agentic AI.
• Geology, resource modeling, mine planning, drilling and blasting, fleet optimization, material movement, mine safety, predictive maintenance, and asset reliability.
• Geoscience and mine systems, fleet management, OT, digital twins, MLOps, model monitoring, responsible AI, cybersecurity, data governance, and operational risk.
• Team leadership, stakeholder management, change management, business value realization, benefits tracking, and performance reporting.

Success measures