Data Scientist

About this role

Data Scientist (Machine Learning for Mine-to-Mill Optimization) Remote | South America Preferred (Chile, Peru, Brazil, Argentina) | Direct Hire We're partnering with an innovative AI company transforming mining operations through machine learning and advanced analytics. Their platform helps mining companies optimize the entire mine-to-mill process, improving recovery, throughput, and operational efficiency through data-driven decision making. The company specializes in applying AI to real-world mining challenges and building production-grade models that continuously evolve as operating conditions change. About the Role We're looking for a Data Scientist with strong machine learning expertise and practical mining industry experience to help build and improve predictive models used across mining and mineral processing operations. This is not a "train once and deploy" environment. You'll develop and maintain models that continuously adapt to changing geological conditions, ore variability, and operational differences across multiple mine sites. You'll work closely with domain experts and engineering teams to deliver measurable improvements in plant performance, recovery, and production outcomes. Mining operations often require ongoing model monitoring and adaptation because ore characteristics and process conditions evolve over time. What You'll Do Build, deploy, and improve machine learning models for mine-to-mill optimization Analyze large-scale mining and processing datasets to identify operational improvement opportunities Develop predictive models related to ore characteristics, fragmentation, recovery, flotation, throughput, and plant performance Monitor model performance and address model drift across sites and changing geological conditions Partner with mining engineers, metallurgists, and operations teams to translate business challenges into ML solutions Work with structured and unstructured industrial datasets to support production decision-making Design exp