Senior Data Scientist - Machine Learning

Placements24; Polokwane; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Health insurance

Hybrid work model

Professional development

Performance bonuses

Job summary

Placements24 in Polokwane is seeking an experienced Senior Data Scientist with a strong background in machine learning to join our innovative research division. The role focuses on developing and deploying advanced predictive models to extract insights from complex datasets and support data-driven decisions.

You will collaborate with domain experts and engineers in a hybrid work setting, tackle challenging analytics projects, and stay current with the latest ML techniques.

Qualifications

• Master's degree or PhD in a quantitative field.
• Minimum 5 years of professional data science experience with ML.
• Proficiency in Python or R and ML libraries.
• Experience with big data tech and cloud platforms.
• Strong problem-solving and communication skills; hybrid Polokwane.

Responsibilities

• Design, develop, and deploy ML models for prediction, classification, and clustering.
• Clean, process, and transform large datasets for analysis and modeling.
• Evaluate model performance and optimize algorithms for accuracy and efficiency.
• Collaborate with research teams to translate business problems into DS solutions.
• Communicate findings through visualizations and reports to stakeholders.
• Stay current with advances in data science, ML, and AI.

Skills

Python

R

Machine Learning

Statistical Modeling

Data Mining

Visualization

Education

Master's degree or PhD in CS/Statistics/Math

Tools

scikit-learn

TensorFlow

PyTorch

Spark

AWS

Azure

Job description

About the Role

Our client is seeking an experienced Senior Data Scientist with a strong background in machine learning to join their innovative research division in Polokwane. This hybrid role involves developing and deploying advanced predictive models and algorithms to extract valuable insights from complex datasets. You will play a critical role in driving data-driven decision-making across various research projects, collaborating closely with domain experts and engineers. This is an exciting opportunity to apply your expertise in a challenging and rewarding environment, contributing to significant scientific advancements within Limpopo.

Key Responsibilities

• Design, develop, and implement sophisticated machine learning models for prediction, classification, and clustering tasks.
• Clean, process, and transform large, complex datasets to prepare them for analysis and modeling.
• Evaluate model performance, conduct rigorous testing, and optimize algorithms for accuracy and efficiency.
• Collaborate with research teams to understand their data needs and translate business problems into data science solutions.
• Communicate findings and model insights effectively through visualizations and reports to both technical and non-technical stakeholders.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.

Requirements

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science, with a focus on machine learning applications.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong understanding of statistical modeling, experimental design, and data mining techniques.
• Experience with big data technologies and cloud platforms (e.g., Spark, AWS, Azure).
• Excellent problem-solving, analytical, and communication skills, comfortable in a hybrid work setting in Polokwane.

Benefits

• Competitive salary package with performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Hybrid work model offering flexibility between office and remote work.
• Opportunities for professional development, training, and attending industry conferences.
• A dynamic and collaborative research environment focused on innovation and data-driven discovery.