Data Scientist

Data Scientist

Qualification & Experience
Minimum

• Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 35 years of experience in data science, analytics, or a related field.
• Proven experience with machine learning, predictive modelling, and statistical analysis.
• Strong proficiency in Python, R, SQL, and data visualisation tools (e.g., Power BI, Tableau).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is advantageous.
• Familiar with version control systems (e.g., Git) and collaborative development practices.

Advantageous

• Masters degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Experience in healthcare, retail, or insurance data ecosystems

Organogram




Objective/Purpose
The Data Scientist is responsible for leveraging advanced analytics, machine learning, and statistical modelling to extract actionable insights from complex datasets. This role supports strategic decision-making, drives innovation, and enhances operational efficiency across the organisation.

Key Performance Areas
Advanced Data Analysis & Modelling

• Develop, implement, and maintain predictive and prescriptive models using machine learning algorithms to forecast business outcomes, enabling proactive decision-making and strategic planning.
• Analyse large and complex datasets using statistical techniques to uncover patterns and trends, driving data-informed insights and operational improvements.
• Monitor model performance using validation metrics and retrain models as needed to maintain accuracy, ensuring continued relevance and reliability of outputs.
• Translate business challenges into analytical problems using structured frameworks, enabling the development of targeted and effective data solutions.

Data Engineering & Management

• Collaborate with data engineers to build robust data pipelines and ensure data integrity.
• Maintain and optimize data storage solutions for scalability and performance.
• Identify opportunities for automation in reporting and analysis using scripting and APIs, increasing efficiency, and reducing turnaround time.
• Document methodologies, assumptions, and outcomes in a clear and reproducible format to support transparency, governance, and knowledge sharing.

Business Intelligence & Strategic Insights

• Translate complex data into actionable insights that support strategic decision-making.
• Identify trends,
  
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