Data Scientist: ML & Insights Leader

Placements24; Upington; On-site; ZAR 700,000 - 1,100,000; Full time

Benefits offered by this job

Competitive salary

Health & retirement benefits

Learning opportunities

Upington collaborative environment

Access to analytics tools

Job summary

Our client in Upington, Northern Cape is seeking a skilled Data Scientist to join the analytics team. You will analyze large datasets, develop predictive models, and drive data-informed decision-making across the organization.

Requirements include a Master's or Ph.D. in a quantitative field, 3+ years of experience, and proficiency in Python or R. Strong communication and collaboration with engineering teams are essential for deploying models into production.

Qualifications

• Master's or PhD in Statistics, Computer Science, Mathematics, or a related quantitative field.
• 3+ years of professional experience as a Data Scientist or in a similar analytical role.
• Proficiency in Python or R.

Responsibilities

• Analyze large, complex datasets to identify trends, patterns, and insights.
• Develop, train, and deploy machine learning models for predictive analytics and forecasting.
• Design and conduct experiments to test hypotheses and evaluate data-driven strategies.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders via visuals and reports.
• Collaborate with engineering teams to integrate data science models into production systems.
• Stay abreast of advancements in data science and ML.

Skills

Python

R

SQL

Machine Learning

Education

Master's or PhD in Statistics/CS/Math

Tools

scikit-learn

TensorFlow

PyTorch

Job description

Our client in Upington, Northern Cape is seeking a skilled Data Scientist to join the analytics team. You will analyze large datasets, develop predictive models, and drive data-informed decision-making across the organization.

Requirements include a Master's or Ph.D. in a quantitative field, 3+ years of experience, and proficiency in Python or R. Strong communication and collaboration with engineering teams are essential for deploying models into production.