Senior Data Scientist

Johannesburg - South Africa

Monthly Salary: Not Disclosed

Posted on: 12 hours ago

Vacancies: 1 Vacancy

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.

Duties and 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.
Collaborate with data engineers to streamline data ingestion and transformation processes using scalable architectures to reduce latency and improve model performance.
Identify and implement novel AI use cases through research and experimentation to enhance business capabilities and competitive advantage.
Communicate complex analytical findings through visualisations and storytelling to influence strategic decisions and operational improvements.
Mentor junior data scientists and analysts through code reviews knowledge sharing and career guidance to build team capability and foster growth.
Contribute to the development of best practices standards and frameworks within the data science team.
Handles ambiguity and setbacks constructively maintaining focus on long-term goals.
Implement responsible AI practices and adhere to data governance policies to maintain trust and regulatory compliance.

Role Competencies:

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

Requirements

Qualification & Experience:

Bachelors degree in Data Science Computer Science Statistics Mathematics or a related field.
68 years of experience in data science with at least 23 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

Benefits

This role follows a hybrid work model allowing flexibility in where you work while requiring in-person presence when operational needs arise.

Required Skills:

Qualification & Experience: Bachelors degree in Data Science Computer Science Statistics Mathematics or a related field. 68 years of experience in data science with at least 23 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