Overview
KoBold Metals is seeking a Senior Data Scientist to join its fast-growing exploration technology team in Lubumbashi, DRC. The role involves developing and applying advanced machine learning and statistical models to support AI-driven mineral exploration. The successful candidate will collaborate with geologists, engineers, and data scientists to solve complex geospatial and physical data problems, driving innovation in the search for critical resources like copper and lithium.

Main Responsibilities
• Develop, test, and deploy predictive models using Python and modern data science libraries.
• Apply statistical, Bayesian inference, and machine learning techniques to diverse physical and geospatial datasets.
• Build tools for geospatial analysis and visualization to support exploration decision-making.
• Leverage cloud computing platforms and collaborative software development practices (git, CICD, testing frameworks).
• Collaborate with interdisciplinary teams to integrate AI solutions into exploration workflows.
• Synthesize and interpret complex datasets to provide actionable insights for mineral discovery.
• Proactively learn new technologies and approaches to enhance exploration efficiency.

Required Qualifications and Skills
• Advanced degree in Data Science, Computer Science, Statistics, Engineering, or related field.
• Strong proficiency in Python and its data science ecosystem.
• Proven experience with predictive modeling, machine learning, and applied statistics (including Bayesian inference).
• Familiarity with collaborative software engineering practices (git, CICD pipelines, testing suites).
• Hands-on experience with cloud computing platforms.
• Expertise in geospatial analysis and visualization.
• Strong problem-solving, prioritization, and communication skills with the ability to work in dynamic, fast-paced environments.
• Eligibility to live and work in the Democratic Republic of Congo.
Preferred (not required): experience in geostatistics, geospatial ML models, image processing, computer vision, or distributed computing applications.