Remote Data Analyst - Geological Data

Placements24; Stellenbosch; Hybrid; ZAR 420,000 - 720,000; Full time

Benefits offered by this job

Competitive salary and incentives

Fully remote with flexible hours

Health, dental, and vision insurance

Generous annual leave and paid timeoff

Professional development opportunities

Job summary

Placements24 in South Africa is seeking a Remote Data Analyst to join their geological data analysis team. You will collect, clean, analyze and interpret large geological datasets to support exploration and resource modeling.

Work with geologists and data scientists to identify trends and insights driving decisions. This fully remote role offers flexible hours and opportunities for professional development.

Qualifications

• Bachelor's degree in Data Science, Statistics, Geology, Computer Science, or a related quantitative field.
• 3+ years of experience in data analysis, with a focus on geological or geospatial data.
• Proficiency in Python (Pandas, NumPy) or R, and SQL databases.
• Familiarity with geological software and data formats is a strong asset.
• Excellent analytical, problem-solving, and communication skills; ability to work independently.

Responsibilities

• Collect, process, and clean large geological and geophysical datasets from various sources.
• Perform statistical analysis and develop predictive models to identify potential mineral deposits.
• Visualize data and create insightful reports and dashboards for technical and non-technical audiences.
• Collaborate with exploration geologists to understand data requirements and interpret results.
• Develop and maintain data quality standards and documentation.
• Identify opportunities for automation and efficiency improvements in data analysis workflows.

Skills

Data analysis

Statistical reasoning

Communication skills

Independent work

Education

Bachelor's degree in a quantitative field

Tools

Python (Pandas, NumPy)

SQL

GIS

Job description

About the Role

Our client is seeking a skilled Remote Data Analyst to join their expanding geological data analysis team, supporting operations in the Western Cape region, including Stellenbosch . In this fully remote position, you will be responsible for collecting, cleaning, analyzing, and interpreting complex geological datasets to support exploration and resource modeling efforts. You will work closely with geologists and other data scientists to identify trends, patterns, and insights that drive critical business decisions. This is an excellent opportunity for a detail-oriented analyst to leverage advanced data techniques in a flexible, remote-first environment.

Key Responsibilities

• Collect, process, and clean large geological and geophysical datasets from various sources.
• Perform statistical analysis and develop predictive models to identify potential mineral deposits.
• Visualize data and create insightful reports and dashboards for technical and non-technical audiences.
• Collaborate with exploration geologists to understand data requirements and interpret results.
• Develop and maintain data quality standards and documentation.
• Identify opportunities for automation and efficiency improvements in data analysis workflows.

Requirements

• Bachelor's degree in Data Science, Statistics, Geology, Computer Science, or a related quantitative field.
• 3+ years of experience in data analysis, with a focus on geological or geospatial data.
• Proficiency in data analysis tools and programming languages such as Python (Pandas, NumPy) or R.
• Experience with SQL databases and data warehousing concepts.
• Familiarity with geological software and data formats is a strong asset.
• Excellent analytical, problem-solving, and communication skills, with the ability to work independently.

Benefits

• Competitive salary and performance-based incentives.
• Fully remote work arrangement with flexible hours.
• Comprehensive health, dental, and vision insurance plans.
• Generous annual leave and paid time off.
• Opportunities for professional development and attending industry conferences.