Remote Data Scientist - Mineral Processing

Placements24; Centurion; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Fully remote

Annual bonus

Professional development budget

Advanced analytics tools

Career growth

Job summary

Placements24 is seeking a highly skilled Remote Data Scientist with expertise in mineral processing to join our technical services team. This fully remote role lets you contribute from anywhere while advancing ore beneficiation and process optimization, using large mining datasets to build predictive models and improve recovery rates.

You will collaborate with metallurgists and engineers, deploy ML models for reagent dosing and throughput, design dashboards, and communicate insights to

Qualifications

• A Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, Chemical Engineering, or related.
• Minimum 5+ years as a Data Scientist with focus on industrial processes, preferably mineral processing or chemical industries.
• Strong programming skills in Python or R, with ML libraries and data visualization expertise.

Responsibilities

• Develop and deploy ML models to predict and optimize mineral processing parameters.
• Analyze large datasets from plant operations and sensors to identify trends and causes of variability.
• Design dashboards to communicate insights to operations and management.
• Collaborate with metallurgists and engineers to validate outputs and integrate solutions.
• Stay updated on AI/ML advancements for mining applications.

Skills

Python

R

SQL

Cloud (AWS/Azure/GCP)

ML libraries

Education

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

Tools

Scikit-learn

TensorFlow

PyTorch

Matplotlib

Plotly

Seaborn

Job description

About the Role

Our client is seeking a highly skilled and motivated Remote Data Scientist with expertise in mineral processing to join their innovative technical services team. This position is fully remote, allowing you to contribute from anywhere while driving advancements in ore beneficiation and process optimization. You will leverage large datasets from various mining operations to develop predictive models, identify operational inefficiencies, and recommend data-driven strategies to improve recovery rates and reduce costs. This role offers a unique opportunity to apply cutting-edge data science techniques to solve complex challenges in the global mining sector, working with a team dedicated to technological advancement.

Key Responsibilities

• Develop and deploy machine learning models to predict and optimize mineral processing parameters (e.g., reagent dosage, throughput, recovery).
• Analyze complex datasets from plant operations, laboratory assays, and sensor data to identify trends and root causes of process variability.
• Design and implement data visualization dashboards to communicate insights to operational teams and management.
• Collaborate with metallurgists and process engineers to validate model outputs and integrate data-driven solutions into plant operations.
• Stay abreast of the latest advancements in data science, AI, and their applications within the mining and mineral processing industries.

Requirements

• Master's or PhD in Data Science, Statistics, Computer Science, Chemical Engineering, or a related quantitative field.
• 5+ years of experience as a Data Scientist, with a demonstrated focus on industrial processes, preferably in mineral processing or chemical industries.
• Strong programming skills in Python or R, including libraries for data manipulation, machine learning (e.g., Scikit-learn, TensorFlow, PyTorch), and visualization (e.g., Matplotlib, Seaborn, Plotly).
• Experience with large-scale data analysis, database querying (SQL), and cloud computing platforms (e.g., AWS, Azure, GCP).
• Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical audiences.

Benefits

• Highly competitive salary and annual bonus structure.
• Fully remote work arrangement, offering flexibility and work-life balance.
• Access to advanced analytics tools and computing resources.
• Professional development budget for courses, conferences, and certifications.
• Be part of a forward-thinking company driving innovation in the mining sector.