The Principal Data Scientist is responsible for developing and deploying advanced analytics, machine learning, and AI capabilities to solve geoscience problems that accelerate mineral exploration and improve decision quality across the Exploration portfolio. As a member of Exploration’s Data Science team, this role partners closely with geoscientist customers, data scientist peers, and technology partners to transform a diverse array of large, complex exploration geoscience datasets into actionable insights and scalable digital solutions that support discovery and boost geological confidence. The position serves as a trusted technical partner to geoscience customers, helping to identify high-value opportunities, frame complex geoscience-centric problems, and translate exploration challenges into practical analytical solutions. Success in this role requires expertise in mathematics, statistics, machine learning, and AI, supported by strong computer science and programming capabilities to ensure solutions are robust, maintainable, and scalable. Success will depend on effective communication with project partners and delivering solutions endorsed by the customer. The successful candidate will bring substantial experience applying machine learning and AI to physical science problems, combining technical excellence with a strong focus on delivering measurable business outcomes, advancing exploration capabilities, and creating value by working with geoscience exploration customers to improve exploration opportunity selection speed and quality.
In this role, you will:
- Lead collaboration with geoscience customers and data scientist peers to develop customized data analytics, machine learning, and AI solutions for large-scale exploration geoscience problems across geology, geochemistry, geophysics, geodynamic modeling, remote sensing, and resource modeling.
- Lead collaboration with the Exploration Technology team to deploy solutions into production environments, ensuring their sustainability and ongoing use beyond initial development.
- Identifying and appropriately applying novel data analytics, machine learning, AI, or computational efficiency opportunities to existing exploration workflows to accelerate the delivery of exploration opportunities through the pipeline and increase the quality of selected opportunities.
- Providing technical leadership and assurance to outsourced data science resources supporting exploration teams to ensure technical work is compliant with internal standards and best practices.
- Define, set, and assure adherence to exploration data science standards and best practices, including code-based workflows or machine learning and AI for geoscientific problems.
- Managing data-science enabling opportunity projects including designing and managing project schedules, budgets, and resourcing.
