Data Scientist - Machine Learning Specialist

Placements24; Pretoria; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary

Health benefits

Learning & development

Hybrid work model

Job summary

Placements24 in Pretoria seeks a Data Scientist specializing in Machine Learning to develop and deploy advanced ML models that solve business problems and drive data-informed decisions. You will work with data engineers, analysts, and stakeholders to translate objectives into scalable ML solutions.

The role emphasizes cutting-edge ML techniques, large datasets, and a hybrid work model with Pretoria-based flexibility. A strong background in ML and statistics is required.

Qualifications

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 3+ years of professional experience in data science with a focus on machine learning.
• Proficiency in Python or R and ML libraries such as TensorFlow, PyTorch, scikit-learn.
• Strong understanding of statistical modeling, data mining, and ML algorithms.
• Experience with big data technologies (Spark, Hadoop) and SQL databases.

Responsibilities

• Develop, train, and deploy ML models for predictive analytics and classification.
• Analyze large datasets to identify patterns and actionable insights.
• Collaborate with data engineers to build data pipelines for training and deployment.
• Evaluate and optimize model performance for accuracy, efficiency, and scalability.
• Communicate findings to technical and non-technical audiences.
• Stay updated with latest ML advancements.

Skills

Python

R

Analytical thinking

Education

Master's or Ph.D. in CS/Statistics/Math

Tools

TensorFlow

PyTorch

scikit-learn

Spark

Hadoop

SQL

Job description

About the Role

Our client is seeking a talented Data Scientist with a specialization in Machine Learning to join their innovative team in Pretoria . In this role, you will be instrumental in developing and deploying advanced machine learning models to solve complex business problems, uncover insights, and drive data-informed decision-making. You will collaborate closely with data engineers, business analysts, and stakeholders to translate strategic objectives into actionable data science solutions. This is an exciting opportunity for a passionate data scientist to leverage cutting-edge ML techniques and large datasets in a challenging and rewarding environment.

Key Responsibilities

• Develop, train, and deploy machine learning models for predictive analytics, classification, and other data-driven applications.
• Analyze large, complex datasets to identify patterns, trends, and actionable insights.
• Collaborate with data engineers to build and maintain robust data pipelines for model training and deployment.
• Evaluate and optimize model performance, ensuring accuracy, efficiency, and scalability.
• Communicate complex findings and model results effectively to both technical and non-technical audiences.
• Stay abreast of the latest advancements in machine learning and data science methodologies.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 3+ years of professional experience in data science, with a strong focus on machine learning.
• Proficiency in programming languages such as Python or R, and expertise in ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of statistical modeling, data mining, and machine learning algorithms.
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases.
• Excellent analytical and problem-solving skills, with the ability to work collaboratively in a team setting.

Benefits

• Competitive salary and performance-based incentives.
• Comprehensive health benefits package including medical, dental, and vision.
• Opportunities for continuous learning and professional development in the field of data science.
• Hybrid work model offering flexibility between office and remote work in Pretoria .
• Access to cutting-edge tools and technologies in a stimulating work environment.