Remote Data Analyst - Mining Operations

Placements24; Vereeniging; Hybrid; ZAR 320,000 - 520,000; Full time

Job summary

Placements24 is seeking a highly analytical Data Analyst to join a mining operations team in a fully remote capacity. You will collect, interpret, and analyze large datasets related to production, efficiency, safety, and exploration, delivering insights to optimize processes and support data-driven decisions across departments.

This role offers remote work flexibility without relocation. The ideal candidate holds a Bachelor's degree in a quantitative field and has proven experience in mining

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• Proven experience as a Data Analyst, preferably within the mining or resources sector.
• Proficiency in data analysis tools and programming languages such as Python (Pandas, NumPy) or R.
• Strong experience with SQL for data extraction and manipulation.
• Expertise in data visualization tools (e.g., Tableau, Power BI).
• Excellent analytical, problem-solving, and communication skills, with the ability to work independently.

Responsibilities

• Collect, clean, and structure data from various mining operational sources (production logs, sensor data, geological surveys).
• Perform statistical analysis to identify trends, patterns, and anomalies in mining operations data.
• Develop and maintain dashboards and reports to visualize KPIs for management.
• Interpret data to provide actionable insights and recommendations for process improvements and cost reductions.
• Collaborate with site operations teams and management to understand data needs and deliver relevant analysis.
• Ensure data integrity and accuracy throughout the analysis process.

Skills

Python

SQL

Tableau

Power BI

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field

Tools

Pandas

NumPy

R

Job description

About the Role

Our client is looking for a highly analytical and self-motivated Data Analyst to join their mining operations team in a fully remote capacity. You will be responsible for collecting, interpreting, and analyzing large datasets related to production, efficiency, safety, and exploration. Your insights will be crucial in identifying trends, optimizing processes, and supporting data-driven decision-making across various departments. This is an exceptional opportunity for a skilled analyst who thrives in a remote work environment and wants to make a significant impact on operational strategy without the need for relocation to Vereeniging .

Key Responsibilities

• Collect, clean, and structure data from various mining operational sources (e.g., production logs, sensor data, geological surveys).
• Perform statistical analysis to identify trends, patterns, and anomalies in mining operations data.
• Develop and maintain dashboards and reports to visualize key performance indicators (KPIs) for management.
• Interpret data to provide actionable insights and recommendations for process improvements and cost reductions.
• Collaborate with site operations teams and management to understand data needs and deliver relevant analysis.
• Ensure data integrity and accuracy throughout the analysis process.

Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
• Proven experience as a Data Analyst , preferably within the mining or resources sector.
• Proficiency in data analysis tools and programming languages such as Python (Pandas, NumPy) or R.
• Strong experience with SQL for data extraction and manipulation.
• Expertise in data visualization tools (e.g., Tableau, Power BI).
• Excellent analytical, problem-solving, and communication skills, with the ability to work independently.

Benefits

• Highly competitive salary and remote work allowance.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and company holidays.
• Opportunities for professional development and online training.
• Flexible working hours within a remote-first culture.