ML Data Scientist: Predictive Analytics & Impact

Placements24; Rustenburg; On-site; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Performance incentives

Health & wellness benefits

Professional development

Job summary

Placements24 in Rustenburg is seeking a highly analytical Data Scientist specializing in Machine Learning to join our innovative team. You will develop and deploy advanced ML models to solve business problems and extract actionable insights from large datasets to drive data-driven decisions.

You will work with domain experts and engineers to build predictive models and ML pipelines, stay current with ML advances, and communicate complex results to both technical and non-technical stakeholders.

Qualifications

• Advanced degree in data science or related quantitative field.
• 3+ years of data science experience with a focus on ML.
• Strong programming in Python or R and ML libraries.

Responsibilities

• Develop, train, and evaluate ML models for predictive analytics, classification, and clustering.
• Prepare data by cleaning and transforming large datasets.
• Design and run A/B tests to validate model performance and impact.
• Collaborate with engineering to deploy models to production.
• Communicate findings via visualizations and reports.
• Keep up with ML/AI advances.

Skills

Python

R

SQL

Statistical modeling

Data mining

A/B testing

Visualization

Problem solving

Education

Master's degree in Data Science or related quantitative field

Ph.D. in Data Science or related quantitative field

Tools

TensorFlow

PyTorch

scikit-learn

Spark

Hadoop

Job description

Placements24 in Rustenburg is seeking a highly analytical Data Scientist specializing in Machine Learning to join our innovative team. You will develop and deploy advanced ML models to solve business problems and extract actionable insights from large datasets to drive data-driven decisions.

You will work with domain experts and engineers to build predictive models and ML pipelines, stay current with ML advances, and communicate complex results to both technical and non-technical stakeholders.