Remote Principal Data Scientist - Mining Analytics

Placements24; Sandton; Hybrid; ZAR 2,600,000 - 4,500,000; Full time

Benefits offered by this job

Stock options

Annual performance bonus

Remote work flexibility

Health, dental, vision insurance

Professional development budget

Job summary

Placements24 is seeking a fully remote Principal Data Scientist to spearhead advanced analytics across mining operations. You will lead predictive maintenance, ore grade optimization, safety analytics, and supply chain efficiency using ML and statistical modeling.

Mentors juniors and collaborates with engineers, geologists, and operations managers, communicating complex findings to executives. This remote-first role requires a strong track record of independent project leadership, cloud

Qualifications

• Advanced degree in a quantitative field (MS/PhD).
• ≥10 years in data science with ML impact.
• Proficiency in Python or R and ML libraries.
• Strong SQL and big data tech (Spark/Hadoop).
• Cloud experience (AWS/Azure/GCP) and data viz basics.
• Leadership and mentoring in remote teams.
• Experience in mining or related industry is a plus.

Responsibilities

• Lead design, development, and deployment of ML models for mining ops.
• Identify challenges where data science adds value.
• Extract, clean, and transform large datasets from sensors/logs.
• Develop predictive, anomaly, forecasting, and optimization models.
• Validate models and present insights to stakeholders.
• Mentor junior data scientists and analysts.
• Collaborate with IT, engineering, operations, and mgmt.
• Stay current with DS/AI advances and apply to mining.
• Develop data pipelines and MLOps for scalable deployment.
• Contribute to data strategy and analytics roadmap.
• Present findings to senior leadership for decision-making.

Skills

Leadership

Communication

Remote work

Python

R

ML/Stat modeling

Time series

Data visualization

Presenting to execs

Education

Master's or PhD in CS/Statistics/DS/Math

Tools

Python

R

scikit-learn

TensorFlow

PyTorch

SQL

Spark

Hadoop

AWS

Azure

GCP

Tableau

Power BI

Job description

About the Role

Our client, a global leader in the mining sector, is seeking an exceptional, fully remote Principal Data Scientist to spearhead their advanced analytics initiatives. This senior role is designed for a visionary individual who can leverage vast datasets to uncover insights, drive operational improvements, and shape strategic decisions across the organization. You will lead projects focused on predictive maintenance, ore grade optimization, safety analytics, and supply chain efficiency using cutting-edge machine learning techniques and statistical modeling. As a Principal Data Scientist, you will mentor junior team members, collaborate with cross-functional teams including engineers, geologists, and operations managers, and communicate complex findings to executive leadership. This is a remote-first position, offering unparalleled flexibility and the opportunity to make a significant impact from anywhere.

Key Responsibilities

• Lead the design, development, and deployment of advanced analytical models and machine learning solutions for mining operations.
• Identify key business challenges and opportunities where data science can provide significant value.
• Extract, clean, and transform large, complex datasets from various sources (e.g., sensors, operational logs, geological data).
• Develop and implement sophisticated algorithms for predictive modeling, anomaly detection, forecasting, and optimization.
• Validate model performance, interpret results, and communicate insights effectively to technical and non-technical stakeholders.
• Mentor and guide junior data scientists and analysts, fostering a culture of innovation and continuous learning.
• Collaborate closely with IT, engineering, operations, and management teams to integrate data-driven solutions into business processes.
• Stay abreast of the latest advancements in data science, machine learning, and AI, and evaluate their applicability to the mining industry.
• Develop and maintain robust data pipelines and MLOps practices for scalable deployment and monitoring of models.
• Contribute to the development of the company's data strategy and analytics roadmap.
• Present findings and recommendations to senior leadership, influencing strategic decision-making.

Requirements

• Master's degree or PhD in Computer Science, Statistics, Data Science, Mathematics, or a related quantitative field.
• A minimum of 10 years of progressive experience in data science and machine learning, with a proven track record of delivering impactful solutions.
• Extensive experience with programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and time series analysis.
• Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and associated data science services.
• Strong understanding of data visualization tools (e.g., Tableau, Power BI) and techniques.
• Demonstrated leadership capabilities and experience mentoring teams.
• Excellent communication, presentation, and interpersonal skills, with the ability to explain complex concepts clearly.
• Experience in the mining or related natural resources industry is highly advantageous.
• Proven ability to work independently and manage projects in a remote setting.

Benefits

• Our client offers a highly competitive salary package, along with a significant annual performance bonus and stock options.
• As a remote position, this role provides exceptional work-life balance and flexibility.
• Comprehensive health, dental, and vision insurance are provided.
• The company invests in professional development, offering a generous budget for training, conferences, and online courses.
• Employees have access to cutting-edge technology and work on challenging, impactful projects that drive innovation in the global mining industry.