Data Scientist - Machine Learning

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

Benefits offered by this job

Hybrid work model

Competitive salary & incentives

Medical, dental, retirement benefits

Advanced computing resources

Learning & growth opportunities

Job summary

Placements24 is seeking a talented Data Scientist with a Machine Learning focus to join our innovative team in Vereeniging. This hybrid role involves building and deploying predictive models, handling large datasets from multiple business units, and collaborating with engineers and domain experts to drive AI-powered solutions.

Requirements include a Master’s or Ph.D. in a quantitative field and proven experience with Python or R and libraries such as Scikit-learn, TensorFlow, and PyTorch.

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with a focus on Machine Learning.
• Proven experience in developing and deploying machine learning models using Python or R with libraries such as Scikit-learn, TensorFlow, PyTorch.
• Strong understanding of statistical modeling, data mining, and algorithm development.
• Experience with data visualization tools and techniques.
• Excellent problem-solving skills and the ability to communicate complex technical concepts clearly.

Responsibilities

• Design, develop, and implement machine learning models for predictive analytics, classification, and clustering.
• Clean, transform, and preprocess large datasets to prepare them for model training and evaluation.
• Evaluate model performance using appropriate metrics and iterate on designs to improve accuracy and robustness.
• Collaborate with software engineers to integrate ML models into production systems and applications.
• Stay abreast of the latest advancements in machine learning and AI, identifying potential applications for the business.

Skills

Python

R

Scikit-learn

TensorFlow

PyTorch

ML algorithms

Statistical modeling

Data visualization

Problem solving

Education

Master's or Ph.D. in quantitative field

Tools

TensorFlow

PyTorch

Job description

About the Role

Our client is seeking a talented Data Scientist with a specialization in Machine Learning to join their innovative team based in Vereeniging . This hybrid role offers the opportunity to develop and deploy advanced predictive models, working on complex datasets from various business units. You will collaborate closely with engineers and domain experts to identify opportunities for AI-driven solutions, enhance decision-making, and optimize operational efficiency. The position is ideal for a candidate passionate about leveraging data to solve real-world problems, contributing to a forward-thinking organization that values data-driven insights and technological advancement within a flexible work structure.

Key Responsibilities

• Design, develop, and implement machine learning models for predictive analytics, classification, and clustering.
• Clean, transform, and preprocess large datasets to prepare them for model training and evaluation.
• Evaluate model performance using appropriate metrics and iterate on model designs to improve accuracy and robustness.
• Collaborate with software engineers to integrate ML models into production systems and applications.
• Stay abreast of the latest advancements in machine learning and artificial intelligence, identifying potential applications for the business.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with a focus on Machine Learning.
• Proven experience in developing and deploying machine learning models using Python or R, along with relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong understanding of statistical modeling, data mining, and algorithm development.
• Experience with data visualization tools and techniques.
• Excellent problem-solving skills and the ability to communicate complex technical concepts clearly.

Benefits

• Highly competitive salary with performance-based incentives.
• Comprehensive medical, dental, and retirement benefits.
• Hybrid work model combining remote flexibility with in-office collaboration in Vereeniging .
• Access to advanced computing resources and development tools.
• Opportunities for continuous learning and professional growth in a rapidly evolving field.