Data Scientist (Machine Learning for Mine-to-Mill Optimization)

Overview

Job Description

Responsibilities

• - 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 experiments and evaluate model performance in real operational environments
• - Contribute to MLOps and model monitoring practices for production systems

Required Skills

• - 5+ years of experience in Data Science, Machine Learning, or Applied AI
• - Strong Python and machine learning fundamentals
• - Experience building production ML systems and maintaining models over time
• - Hands-on experience with: Google Cloud Platform (GCP), BigQuery, Parquet-based data pipelines, Model monitoring and performance tracking
• - Strong statistical modeling and experimentation skills
• - Experience working with large operational or industrial datasets
• - Excellent communication skills and ability to collaborate with cross-functional teams
• - Direct experience in mining, mineral processing, metallurgy, or mine-to-mill optimization (strongly preferred)
• - Understanding of: Ore variability, Rock hardness and fragmentation, Flotation processes, Recovery optimization, Mill performance drivers, Production process analytics
• - Experience supporting multiple operational sites with varying geological conditions
• - Experience with time-series modeling and industrial process optimization (nice to have)
• - Experience with MLOps frameworks (nice to have)
• - Knowledge of process control systems and industrial data platforms (nice to have)
• - Experience with predictive maintenance or optimization systems (nice to have)
• - Background in copper, gold, or base metals operations (nice to have)

Benefits

• - Competitive compensation (~USD $140,000/year, depending on experience)
• - Fully remote
• - Opportunity to work on cutting-edge AI applications in the mining industry
• - Small, highly technical team with direct impact on product and customer outcomes
• - Fast-moving hiring process