7 Data Science jobs in Western Cape
COO (Data Science)
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- Application Deadline: 29 October 2025
- Job Location: Stellenbosch, Western Cape
- Job Title: COO (Data Science)
- Education Level: Bachelors Degree
- Job Level: Management
- Minimum Experience: Years
Duties and Responsibilities:
- Working as part of a high-performance, service-driven group that prides itself on attracting the finest talent, you will find yourself in an environment buzzing with energy, where smart, motivated people collaborate to deliver the best data and technology solutions.
- Will also coordinate the integration of various software systems and collaborate with teams across business units and countries to enable data-driven solutions, improve business processes, and support informed decision-making.
Requirements:
- A degree in a relevant field of study, such as data science, statistics, engineering, or computer science
- At least ten years' experience in relevant fields, including data, analytics, data science, software development, and/or engineering
- Experience in people management and leadership
- Familiarity with CRM software (e.g., HubSpot, Salesforce)
- Advanced understanding of BI and analytics tools (e.g., Tableau, Power BI, Google Analytics)
- Familiarity with data science tools and programming languages (e.g., R, Python, MATLAB, pandas) as well as database languages
- Knowledge of data pipelines and data integrations
- Proven experience in building a data strategy and executing projects, including data science and AI applications
- Experience managing technology projects and product development
- Ability to identify and communicate value-adding, data-driven insights to influence marketing, e-commerce, and broader business decisions
- Strong communication skills across all levels of the organisation
- Willingness to travel internationally
- Availability to work on-site, five days per week
- Knowledge of GDPR and POPIA, with experience implementing compliance measures across business operations
- Experience in e-commerce
- Proactive, creative, and able to take initiative
Lecturer - Module Coordinator Data Science
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Key Roles and Responsibilities:
Study material development
Oversee and manage the development or review of study guides (full or wrap-around)
Seek feedback from all stakeholders and keep a record of required changes to study guides in anticipation of the review cycle
Monitor the appropriateness of the prescribed textbook and editions
Ensure continued alignment between study guide and textbook, where applicable
Update study guides to cater for new textbook editions
Assessment
Draft all formal assessments for allocated modules
Consider internal and external pre-moderation feedback and implement changes as required
Conduct internal pre-moderation for modules in field of expertise
Conduct annual meetings with all campus lecturers to discuss the assessment strategy
Appoint suitably qualified internal and external moderators
Brief markers and moderators, and provide content support during the marking process
Mark a prescribed minimum number of assessments to fine tune marking guideline/memorandum
Consider markers' reports and decide on appropriate action
Consider moderators' reports and decide on appropriate action, in consultation with campus lecturers, HOS and subject coordinator (if any)
Conduct post-assessment meetings with all campus lecturers to reflect on success/concerns with assessments
Consider and analyse cross-campus success rates
Sign off on assessment results
Actively participate in the investigation/management of Red/Fire module status
Learning Journey Design
Conduct research in the field of expertise and/or learning design in the field of expertise
Attend both internal and external training sessions, workshops, and conferences to enhance skills in module design and assessment
Stay informed about emerging trends in higher education and instructional methodologies
Engage with industry, professional networks and associations to enhance collaboration and knowledge sharing
Actively collaborate with campus lecturers to continuously enhance the learning journey
LMS course environment
Design and draft materials needed for the course environment (announcements, etc.)
Populate and maintain the Canvas Blueprint course environment for modules owned
Lecturer and student support
Develop and deliver at least two lectures per module per semester for CL students, online live
Record at least two online lectures for DL students per semester per module
Deliver guest lectures in the field of expertise on STADIO modules as appropriate
Research and Professional Development
Conduct research in the field of expertise and/or learning design in the field of expertise
Attend both internal and external training sessions, workshops, and conferences to enhance skills in module design and assessment
Stay informed about emerging trends in higher education and instructional methodologies
Engage with industry, professional networks and associations to enhance collaboration and knowledge sharing
REQUIREMENTS
Minimum Requirements and Qualifications
Master's degree in Data Science, Statistics, Computer Science, or a related discipline .
A Doctoral degree will be an advantage
At least 5 years' Higher Education experience in Data Science or Analytics.
Strong knowledge of Python, R, machine learning, statistical modelling, and big data tools .
Industry or research experience in applying data science to real-world problems.
Key Attributes:
Ability to balance theoretical foundations with applied industry-relevant case studies.
Strong quantitative and computational thinking.
Ability to coordinate modules that articulate into postgraduate Data pathways.
Engagement with professional and industry networks to keep content current.
Machine Learning Engineer 10027
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Job description:
Join Us in Becoming the Best Bank in the World
We appoint energized and motivated people for their potential and continuously look for talented, driven individuals to help us innovate and evolve. That is why we focus on finding the right people for the right jobs. We love what we do because we focus on making a positive difference for our clients and employees. Our company DNA is built around talented and committed teams dedicated to build a brand that we are proud of and earns the trust of our clients.
Who we are:
We are a bank, but we're much more than that. We believe that banking is about enabling people to control their financial lives through banking that is simplified, accessible, affordable and delivered through personal experience. By helping our clients manage their financial lives better, we enable them to live better.
Why choose us:
At Capitec, we offer our best by living up to our CEO values in every situation – we always put the Client first, act with Energy and take Ownership. And to support people in being their best, our Employee Value Proposition offers every value to all team members through cohesive teams, growth opportunities as well as employee benefits and savings. We make it a priority to ensure that each member of the Capitec team feels welcome, valued, focused, and has the opportunity to grow.
About the role:
As a Machine Learning Engineer at Capitec is pivotal in shaping and executing the bank's AI strategy. By collaborating with Data Scientists and Decision Scientists, you'll enhance their efficiency through the development, implementation, and support of platform improvements. Your contributions will be crucial in positioning Capitec to remain competitive in a rapidly evolving landscape where AI technologies are key strategic differentiators.
This role leverages your deep understanding of machine learning models, from concept to deployment, and expertise in modern software development best practices, big data processing frameworks, and cloud environments whilst sitting in the risk division of the business. You'll also be working extensively with Python, SQL, and advanced debugging techniques to ensure the delivery of scalable, robust, and production-ready predictive models
Our ideal candidate has:
- 4+ years of experience in any engineering role
- Honors degree or higher in any field
- Python and SQL experience
- TensorFlow, PyTorch, Scikit-learn, XGBoost, Hugging Face, LangChain, LangGraph, MLflow, RAG, and Transformers
- Big data frameworks – Hadoop/Kafka (PySpark)
- Github experience or Git
- AWS experience: S3, Redshift, SageMaker, Bedrock, Lambda
Competencies:
- Simplify and make it easy
- Earn and extend trust
- Plan, deliver and raise the bar
- Curious and continuously learns
- Act, learn and adapt
- Inspire optimism and persistence
- Have courage, disagree and commit
Education:
- Completed an Honors Degree or higher
If you are interested in being part of this dynamic team, on a mission to build the best bank in the world through unlocking the potential of its people, please apply. We would love to hear from you
Capitec is committed to diversity and, where feasible, all appointments will support the achievement of our employment equity goals
Machine Learning Engineer (Specialist)
Posted 5 days ago
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Specialist Machine Learning Engineer
Posted 10 days ago
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The Specialist Machine Learning Engineer is responsible for advancing the organisation’s technical capabilities in specific, high-impact areas of machine learning such as natural language processing (NLP), computer vision, or reinforcement learning. This role combines deep research expertise with practical engineering skills to design, prototype, and deploy innovative ML solutions that address complex, domain-specific business challenges. The incumbent serves as a subject-matter expert and innovation driver, ensuring that the organisation remains at the forefront of emerging ML technologies and methodologies.
Key Responsibilities:
Focus on niche areas of machine learning, such as NLP, computer vision, or reinforcement learning, to deliver specialised solutions.Develop and refine domain-specific ML models tailored to unique business needs, leveraging advanced algorithms and architectures.Conduct in-depth research, feasibility studies, and prototyping of innovative ML approaches using cutting-edge methods and tools.Identify opportunities to apply the latest advancements in machine learning to enhance processes, improve decision-making, or create new business capabilities.Work closely with other ML Engineers, Data Scientists, and Software Engineers to transfer research insights into scalable, production-ready solutions.Provide expert-level insights on specific ML tools, frameworks, or algorithms, guiding the organisation in adopting best-in-class technologies.Contribute to the design and development of internal ML tools, utilities, and libraries to streamline experimentation, model management, and deployment workflows.RequirementsNQF Level 6 or higher tertiary qualification in an Information and Communication Technology (ICT) field (e.g., Computer Science, Information Systems, Data Science, or related discipline).Cloud certification (AWS, Azure, or GCP) preferred.Minimum of 6 years’ experience in a Machine Learning Engineer or related advanced AI/ML role.Proven expertise in one or more ML specialisations (e.g., NLP, computer vision, or reinforcement learning).Strong background in research, experimentation, and model deployment.Demonstrated ability to translate research into practical, high-performance production systems.Intermediate Machine Learning Engineer
Posted 10 days ago
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The Intermediate Machine Learning Engineer is responsible for developing, optimizing, and deploying machine learning solutions that support data-driven decision-making and business objectives. The role requires strong technical expertise in model development, pipeline management, and integration within production environments.
Key Responsibilities:
The role encompasses many activities, including (but not limited to):Building and maintaining end-to-end machine learning pipelines for model development, training, testing, and deployment.Training and fine-tuning ML models using structured and unstructured datasets.Collaborating with Senior Engineers and Data Scientists to implement ML models into production environments.Conducting model evaluation and validation to ensure accuracy, scalability, and alignment with business goals.Troubleshooting and resolving issues related to model performance, accuracy, and deployment.Documenting workflows, maintaining version control, and ensuring reproducibility of ML experiments.Supporting the integration of ML models with existing software systems and data infrastructures.Keeping up-to-date with emerging tools, frameworks, and trends in machine learning and AI.RequirementsNQF Level 6 or higher tertiary qualification in an ICT-related field, such as Information Systems, Computer Science, Data Science, Software Engineering.Preferred Certifications: Cloud platform certification (AWS, Azure, or GCP) with specialization in ML or AI services.Minimum of 3 years’ experience in a Machine Learning Engineer role or a similar position.Proven experience developing, deploying, and monitoring machine learning models in production.Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Experience with cloud-based ML services and tools (AWS SageMaker, Azure ML, GCP Vertex AI).Familiarity with containerization (Docker, Kubernetes) and CI/CD practices for ML OpsStrong programming skills in Python (and optionally R or Java).Proficiency in data preprocessing, feature engineering, and model evaluation techniques.Experience working with APIs and integrating ML models into production systems.Solid understanding of software engineering principles and version control (Git).Strong analytical, problem-solving, and debugging skills.Excellent collaboration and communication abilities within cross-functional teams.Senior Machine Learning Engineer
Posted 10 days ago
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The Senior Machine Learning Engineer is responsible for designing, developing, and deploying advanced machine learning solutions that drive business impact. This role requires deep technical expertise, strong problem-solving skills, and the ability to lead complex projects from conception through to production. The incumbent will play a key role in shaping the organisation’s ML strategy, mentoring junior engineers, and ensuring scalable, efficient, and ethical use of AI technologies.
Key Responsibilities:
Design and implement advanced machine learning models and systems to solve complex business challenges. Lead the end-to-end lifecycle of ML projects, including data preparation, model training, validation, deployment, and ongoing monitoring. Optimise existing ML models and pipelines for scalability, efficiency, and performance in production environments. Partner with data engineers, software developers, and business stakeholders to integrate ML solutions seamlessly into existing systems and workflows. Provide mentorship, guidance, and technical leadership to mid-level and junior ML engineers to ensure knowledge sharing and adherence to best practices. Develop, maintain, and enforce standards for model governance, documentation, versioning, and reproducibility. Stay abreast of emerging trends, tools, and technologies in machine learning, MLOps, and AI ethics to continually improve solutions and frameworks.RequirementsNQF Level 6 or higher tertiary qualification in an ICT-related field (e.g., Computer Science, Information Systems, Data Science, or related discipline).Cloud certification (e.g., AWS, Azure, or GCP) preferred. Minimum of 5 years’ experience in a Machine Learning Engineer or similar role.Proven track record of designing, developing, and deploying ML models in production environments.Experience with modern ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).Solid understanding of data engineering, model lifecycle management, and MLOps practices.Be The First To Know
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