Senior Data Scientist

Job Summary

The Senior Data Scientist will lead the design, development, and deployment of advanced analytics and machine learning solutions that drive strategic decision-making and operational efficiency. This role requires a deep understanding of data science, data engineering, and AI concepts, and will play a pivotal role in embedding intelligent automation and predictive modelling across the organisation.

Responsibilities:

• Build and implement machine learning models using structured and unstructured data to improve forecasting accuracy and enable proactive decision-making.
• Optimise model performance and scalability through hyperparameter tuning and algorithm selection to enhance efficiency and reduce computational costs.
• Implement reproducible research practices by using version control, documentation, and testing to maintain model integrity and facilitate collaboration.
• Monitor deployed models in production using performance metrics and alerting systems to ensure reliability and timely intervention.
• Automate repetitive data science tasks through scripting and workflow orchestration to increase productivity and reduce manual errors.
• Maintain high data quality standards by conducting regular audits and validation checks to support trustworthy analytics.
• Translate complex analytical findings into clear, actionable insights for non-technical stakeholders to drive informed business strategies.
• Present data-driven recommendations using compelling visualisations and storytelling techniques to influence executive decision-making.
• Collaborate with stakeholders to define key metrics and success criteria to align analytics efforts with business goals.
• Identify and implement novel AI use cases through research and experimentation to enhance business capabilities and competitive advantage.
• Implement responsible AI practices and adhere to data governance policies to maintain trust and regulatory compliance.

Qualifications:

• Matric and a Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 8+ years of experience in data science, with at least 3 years in a senior or lead role.
• Proven experience in developing and deploying machine learning models in production environments.
• Strong proficiency in Python, R, SQL, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Solid understanding of data engineering principles and cloud data architectures (e.g., Azure, AWS, GCP).
• Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow).
• Excellent communication and stakeholder engagement skills.

Advantageous

• Masters degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Experience with large language models (LLMs) and generative AI.
• Experience in healthcare, retail, or insurance data ecosystems

Technical Skills:

Machine Learning

• Expert in designing, developing, and deploying advanced machine learning and AI models.
• Expert in selecting appropriate algorithms, optimising model performance, and mentoring junior team members in best practices.

Data Engineering & Architecture

• Understanding of ETL/ELT processes and data pipeline design.
• Ability to collaborate with data engineers to ensure data quality and accessibility.

Programming & Tooling

• Advanced proficiency in Python, R and SQL
• Use of Jupyter, VS Code, Git, and other development tools.
• Contribute to code reviews and promotes clean, maintainable code practices

Cloud-Native ML Tools & Platforms

• Proficiency in deploying models using platforms like AWS SageMaker, Azure ML, or Google Cloud AI Platform.
• Familiarity with containerisation (Docker) and orchestration (Kubernetes) for scalable ML solutions.

Data Visualisation and Storytelling:

• Effectively communication of complex analytical insights through compelling visualisations and narratives