Remote Lead Mining Data Scientist: ML-Driven Analytics

Placements24; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Job description

About the Role

Our client is seeking a visionary and experienced Remote Lead Mining Data Scientist to establish and lead their advanced analytics initiatives. This role is critical in leveraging big data to drive operational efficiencies, optimize resource extraction, and inform strategic decision‑making across all mining operations. You will work with vast datasets from exploration, production, and processing to build predictive models, develop data‑driven insights, and guide the implementation of data science solutions. The ideal candidate thrives in a remote setting, possesses deep expertise in data science and machine learning, and has a strong understanding of the mining industry's unique challenges and opportunities.

Key Responsibilities

• Lead the development and deployment of machine learning models for predictive maintenance, resource forecasting, and operational optimization.
• Design and implement data pipelines for collecting, cleaning, and transforming large-scale mining datasets.
• Develop advanced analytical techniques to uncover patterns and insights from geological, operational, and financial data.
• Collaborate with domain experts (geologists, engineers, metallurgists) to define analytical problems and deliver actionable solutions.
• Mentor and guide a team of data scientists and analysts in a remote work environment.
• Stay at the forefront of data science and AI advancements, identifying opportunities for application in the mining sector.

Requirements

• PhD or MSc in Data Science, Computer Science, Statistics, or a related quantitative field.
• Minimum of 8 years of experience in data science, with at least 3 years in a leadership role.
• Proven experience applying machine learning techniques (e.g., regression, classification, clustering, deep learning) to complex problems.
• Proficiency in programming languages such as Python or R, and experience with data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Strong understanding of the mining industry's data landscape and challenges.

Benefits

• Highly competitive salary and significant performance‑based bonuses.
• Comprehensive health, dental, and vision insurance.
• Flexible remote work arrangement with generous home office support.
• Access to cutting‑edge technology and a significant budget for professional development.
• A stimulating and collaborative virtual work environment focused on innovation and impact.