Remote Lead Data Scientist (Mining Analytics)

Placements24; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Home office stipend

Health insurance

Retirement benefits

Conference access

Professional certifications

Flexible hours

Cutting-edge tools

Job summary

Placements24 is partnering with a forward-looking mining corporation to hire a remote Lead Data Scientist specializing in mining analytics. You will lead a team, mentor peers, and translate complex data into actionable business insights across exploration, production, maintenance and safety.

Responsibilities include building predictive models for ore grade and equipment reliability, designing scalable data pipelines, and presenting findings to senior leadership.

Qualifications

• Master's degree or PhD in a quantitative field.
• 8+ years in data science/advanced analytics; 3+ in leadership.
• Proven experience with ML techniques (regression, classification, clustering, deep learning).
• Proficiency in Python or R and libraries (TensorFlow, PyTorch, Scikit-learn, Pandas).
• Experience with big data (Spark, Hadoop) and SQL/NoSQL databases.
• Strong statistical modeling, experimental design, and hypothesis testing.
• Mining or natural resources sector experience is desirable.
• Excellent communication and remote-stakeholder management skills.
• Demonstrated leadership and mentorship of teams.

Responsibilities

• Lead development and deployment of predictive models for ore grade, equipment failure, production optimization, and safety risk.
• Design and implement ML algorithms and statistical techniques for large-scale mining data from sensors, surveys, and logs.
• Develop and maintain robust data pipelines with data quality and accessibility.
• Create data visualizations and dashboards to communicate insights to stakeholders at all levels.
• Mentor and guide a team of data scientists and analysts; foster best practices.
• Collaborate with geologists, mining engineers, and operations managers to translate business problems into data projects.
• Stay updated on advances in data science and mining applications.
• Manage data science projects from conception to deliverables with clear scope and timelines.
• Develop data governance, security, and ethical use strategies.

Skills

Machine learning

Statistical modeling

Data visualization

Leadership

Mentoring

Stakeholder communication

Business acumen

Education

Master's degree or PhD in Data Science or related field

Tools

Python

R

TensorFlow

PyTorch

Scikit-learn

Pandas

Spark

Hadoop

SQL

NoSQL

Job description

About the Role

Our client, a forward-thinking mining corporation, is seeking a highly skilled and experienced Remote Lead Data Scientist specializing in Mining Analytics to join their innovative team. This is a completely remote position, offering a unique opportunity to drive data-driven decision-making across global mining operations without geographical constraints. You will be responsible for developing and implementing advanced analytical models to extract actionable insights from vast datasets related to exploration, production, maintenance, and safety. The ideal candidate will possess a strong background in machine learning, statistical modeling, and data visualization, with a proven ability to translate complex data into clear business strategies. You will lead a team of data scientists, mentor junior analysts, and collaborate closely with operational and technical departments to identify key challenges and opportunities where data science can provide solutions. This role demands exceptional problem-solving skills, a deep understanding of the mining lifecycle, and the ability to communicate technical findings effectively to both technical and non-technical stakeholders. Join us to shape the future of mining through cutting-edge data science in a fully flexible, remote setting.

Key Responsibilities

• Lead the development and deployment of predictive models for ore grade, equipment failure, production optimization, and safety risk assessment.
• Design and implement machine learning algorithms and statistical techniques to analyze large-scale mining data from various sources (e.g., sensors, geological surveys, operational logs).
• Develop and maintain robust data pipelines, ensuring data quality, integrity, and accessibility for analysis.
• Create compelling data visualizations and dashboards to communicate insights and trends to stakeholders at all levels.
• Mentor and guide a team of data scientists and analysts, fostering technical growth and best practices.
• Collaborate with geologists, mining engineers, and operations managers to identify business problems and translate them into data science projects.
• Stay abreast of the latest advancements in data science, machine learning, and their applications within the mining industry.
• Manage data science projects from conception to completion, including defining project scope, timelines, and deliverables.
• Develop strategies for data governance, security, and ethical use of data within the organization.
• Present findings and recommendations to senior leadership, influencing strategic decision-making.

Requirements

• A Master's or Ph.D. degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• A minimum of 8 years of experience in data science or advanced analytics, with at least 3 years in a leadership or senior role.
• Proven experience applying machine learning techniques (e.g., regression, classification, clustering, deep learning) to real-world problems.
• Proficiency in programming languages such as Python or R, and associated data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas).
• Experience with big data technologies (e.g., Spark, Hadoop) and database management (SQL, NoSQL).
• Strong understanding of statistical modeling, experimental design, and hypothesis testing.
• Experience in the mining or natural resources sector is highly desirable.
• Excellent communication, presentation, and stakeholder management skills, essential for a remote role.
• Demonstrated ability to lead projects and mentor team members.
• Strong business acumen and the ability to connect data insights to business value.

Benefits

• Highly competitive salary package with significant performance incentives.
• Remote work flexibility with a generous home office stipend.
• Comprehensive health insurance and retirement benefits.
• Opportunities for continuous learning, attending conferences, and professional certifications.
• Access to cutting-edge tools and technologies.
• Work on impactful projects that drive innovation in the mining industry.
• Flexible working hours.