Lead Data Scientist - Mining Analytics (Remote)

Placements24; Pretoria; Hybrid; ZAR 1.200.000 - 2.000.000; Vollzeit

Benefits dieser Stelle

Home office stipend

Flexible working hours

Remote work

Health & wellness programs

Zusammenfassung

Placements24 is seeking a Lead Data Scientist - Mining Analytics for a fully remote role overseeing advanced data initiatives across global mining operations. You will spearhead data science efforts, crafting predictive models and ML solutions to optimize exploration, extraction, processing, and safety.

You'll lead a team of data scientists, partner with geologists, engineers, and operations managers, and translate insights into actionable business strategies using dashboards and scalable data

Qualifikationen

• Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, or related field.
• A minimum of 7 years of professional data science and ML experience.
• Experience with Python or R and ML libraries (TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Proficiency in SQL and big data tech (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Strong understanding of statistical modeling and ML techniques; design of experiments.
• Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn).
• Excellent leadership and communication skills; ability to influence stakeholders.
• Familiarity with mining or related industries is advantageous.
• Ability to work independently in a remote setting.

Aufgaben

• Lead design, development, and deployment of advanced analytical models for mining applications.
• Ingest, clean, and transform large datasets from geological surveys, sensor data, and operations.
• Develop predictive models for resource estimation, equipment failure, process optimization, and safety risk assessment.
• Build and maintain data pipelines and real-time analytics infrastructure.
• Create dashboards and presentations to communicate findings to technical and non-technical stakeholders.
• Mentor a team of data scientists and collaborate with geologists, engineers, and managers.
• Stay updated on ML advancements and assess applicability to mining.
• Ensure ethical and responsible use of data and AI technologies.

Kenntnisse

Leadership

Communication

Independent work

Remote collaboration

Ausbildung

Master's degree or PhD in a quantitative field

Tools

Python

R

TensorFlow

PyTorch

scikit-learn

SQL

Spark

Jobbeschreibung

About the Role

Our client, a forward-thinking leader in the global mining sector, is looking for an exceptional Lead Data Scientist - Mining Analytics to spearhead their advanced data initiatives. This is a fully remote opportunity, allowing you to leverage your expertise in data science to drive significant improvements across our mining operations worldwide. You will be responsible for developing and implementing sophisticated analytical models and machine learning solutions to optimize exploration, extraction, processing, and safety. This role demands a strategic thinker with a passion for uncovering insights from complex datasets, building robust predictive models, and translating data-driven findings into actionable business strategies. You will lead a team of data scientists, collaborating closely with geologists, engineers, and operational managers to unlock the full potential of our vast data resources.

Key Responsibilities

Lead the design, development, and deployment of advanced analytical models and machine learning algorithms tailored for mining applications. Extract, clean, and transform large, complex datasets from various sources, including geological surveys, sensor data, operational logs, and production reports. Develop predictive models for resource estimation, equipment failure prediction, process optimization, and safety risk assessment. Build and maintain data pipelines and infrastructure to support real-time analytics and reporting. Visualize and communicate complex findings and insights to both technical and non-technical stakeholders through compelling dashboards and presentations. Mentor and guide a team of data scientists, fostering a collaborative and innovative environment. Collaborate with cross-functional teams to identify business opportunities where data science can provide significant value. Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, and assess their applicability to the mining industry. Ensure the ethical and responsible use of data and AI technologies.

Requirements

A Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. A minimum of 7 years of professional 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 libraries like TensorFlow, PyTorch, scikit-learn, pandas, and NumPy. Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP). Strong understanding of statistical modeling, machine learning techniques (supervised and unsupervised learning), and experimental design. Experience in data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn). Excellent leadership, communication, and interpersonal skills, with the ability to effectively lead a team and influence stakeholders. Familiarity with the mining industry or related domains (e.g., oil & gas, natural resources) is a significant advantage. Ability to work independently and manage multiple projects in a remote setting.

Benefits

Our client offers a highly competitive salary, significant bonus potential, and excellent remote work benefits, including a home office stipend and flexible working hours. You will be part of a cutting-edge team driving digital transformation in the mining sector, with ample opportunities for professional growth and skill development. Comprehensive health and wellness programs are provided. This role offers the chance to make a substantial impact on global mining operations from the comfort of your home office, contributing to a more efficient, safer, and sustainable industry.