Remote Lead Data Scientist - Predictive Mining Analytics

About the Role

Our client, a global leader in resource extraction, is looking for an exceptional Lead Data Scientist to spearhead their innovative Predictive Mining Analytics initiative. This is a fully remote position, allowing you to contribute your expertise from anywhere. You will be instrumental in developing and deploying advanced machine learning models to optimize exploration, extraction, and operational efficiency across diverse mining sites. This role requires a deep understanding of data science methodologies, a passion for solving complex real-world problems, and the ability to lead and mentor a team of data scientists. You will work with vast datasets, leveraging cutting-edge technologies to drive data-informed decision-making and unlock new efficiencies in the mining sector.

The primary focus will be on building robust predictive models for resource estimation, equipment maintenance, and production forecasting.

Key Responsibilities

• Lead the design, development, and implementation of predictive models for mining operations using machine learning and statistical techniques.
• Analyze large, complex datasets from various sources, including geological surveys, sensor data, and operational logs.
• Develop and refine algorithms for resource estimation, ore grade prediction, and mineral identification.
• Build predictive maintenance models for mining equipment to minimize downtime and optimize service schedules.
• Create models to forecast production volumes, energy consumption, and environmental impact.
• Collaborate with geologists, mining engineers, and operations managers to translate business needs into data science solutions.
• Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
• Communicate complex analytical findings and recommendations clearly to both technical and non-technical stakeholders.
• Evaluate and implement new data science tools, technologies, and methodologies.
• Ensure the scalability, reliability, and performance of deployed models in a cloud environment.

Requirements

• Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with at least 3 years in a leadership or senior role.
• Proven experience in building and deploying machine learning models for time-series forecasting, classification, and regression problems.
• Strong proficiency in Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
• Solid understanding of statistical modeling, experimental design, and hypothesis testing.
• Experience within the mining industry or a related heavy industry is highly advantageous.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to a diverse audience.
• Demonstrated ability to lead and mentor a technical team.

Benefits

As this is a fully remote position, we offer unparalleled flexibility and work-life balance. Our client provides a highly competitive salary, performance-based bonuses, and a comprehensive benefits package including health insurance and retirement savings plans. You will have access to continuous learning opportunities, cutting-edge technologies, and the chance to make a significant impact on the future of the mining industry. Join a forward-thinking company that values data-driven innovation and empowers its remote workforce.