Remote Data Scientist - Mineral Resource Modeling

Placements24; Stellenbosch; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Fully remote work

Flexible hours

Home office setup allowance

Professional development resources

Job summary

Placements24 is seeking a highly skilled Remote Data Scientist to join a global team focused on advanced mineral resource modeling. This fully remote role enables you to work from anywhere while contributing to geological data analysis and predictive modeling.

You will leverage ML and statistical techniques to enhance resource estimation, exploration targeting, and mine planning, collaborating with geologists, engineers, and other data scientists across borders.

Qualifications

• Master's degree or PhD in a quantitative field.
• 5+ years of experience as a Data Scientist with ML portfolio.
• Proficiency in Python or R and ML libraries.
• Experience with databases and big data platforms.
• Familiarity with geological concepts is a plus.
• Strong remote collaboration and communication skills.

Responsibilities

• Develop and implement advanced statistical and ML models for mineral resource estimation.
• Analyze large datasets from geological surveys, drilling data, and logs.
• Build predictive models to identify exploration targets and optimize drilling strategies.
• Collaborate remotely with geologists, engineers, and data scientists to define requirements.
• Create data visualizations and dashboards to communicate findings to stakeholders.
• Stay updated on ML and geospatial data science advancements.

Skills

ML models

Python/R

SQL/NoSQL

Data Visualization

Remote collaboration

Education

Master's or PhD in Data Science / Statistics / CS

Tools

Scikit-learn

TensorFlow

PyTorch

SQL

NoSQL

Job description

About the Role

Our client is seeking a highly skilled and analytical Remote Data Scientist to join their global team, focusing on advanced mineral resource modeling. This position is fully remote, allowing you to work from anywhere while contributing to cutting-edge geological data analysis and predictive modeling. You will leverage machine learning and statistical techniques to enhance the accuracy and efficiency of resource estimation, exploration targeting, and mine planning. This is a unique opportunity for a data expert to make a significant impact in the mining industry without the need for on-site presence, working with a collaborative and innovative international team.

Key Responsibilities

• Develop and implement advanced statistical and machine learning models for mineral resource estimation and geological characterization.
• Analyze large datasets from various sources, including geological surveys, drilling data, and geophysical logs.
• Build predictive models to identify promising exploration targets and optimize drilling strategies.
• Collaborate remotely with geologists, engineers, and other data scientists to define project requirements and interpret results.
• Create data visualizations and dashboards to communicate complex findings to both technical and non-technical stakeholders.
• Stay abreast of the latest advancements in data science, machine learning, and their applications in the mining sector .

Requirements

• Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Proven experience (5+ years) as a Data Scientist, with a strong portfolio of applied ML projects.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with database technologies (SQL, NoSQL) and big data platforms.
• Familiarity with geological concepts and mineral resource modeling principles is a significant advantage.
• Excellent communication and collaboration skills for effective remote teamwork.

Benefits

• Competitive salary commensurate with experience and qualifications.
• Fully remote work arrangement with flexible hours.
• Generous home office setup allowance.
• Access to professional development resources and online courses.
• Opportunity to work on challenging, impactful projects at the forefront of geospatial data science .