1,069 Scientific Research & Development jobs in South Africa

Role Purpose

To deliver high-quality research through the planning and execution of broiler and breeder trials, to ensure bird performance optimisation aligned with our strategic objectives.

Aligned with Astral's best cost and operational excellence, the R&D Manager optimises broiler production through trial management and protocol adherence, supporting sustainability and growth strategies.

• Design and implementation of trial protocols.
• Conduct broiler trails accurately according to protocol.
• Accurate trial feed formulations.
• Innovate and optimise broiler trial methodologies.
• Implement waste reduction in trial processes.
• Drive adoption of technology in trials.
• Lead broiler production unit management initiatives.
• Foster supplier development for trial facilities.
• Ensure compliance with bio-security and health management.
• Precise data collection and analysis.

Role Requirements:

• Minimum qualification: MSc in Agric Animal Science or in progress of obtaining the qualification.
• Advantage: Diploma in Data Analytics.

• Total of 2 years minimum work experience.
• Minimum of 2 years experience working in Agriculture & FMCG environment.
• Minimum of 2 years experience in trial feed formulation.
• Minimum of 2 years experience in conducting scientific broiler trials and the interpretation of results.
• Minimum of 2 years experience in managing a broiler production units.

• Poultry health and bio-security protocols.
• Feed formulation and techniques.
• Poultry management.
• Broiler performance testing.
• Research methodology.
• Data analysis.

Apply by :

We're on the lookout for energetic, self-motivated individuals who share our passion for service in the banking industry. To be part of the journey, follow the steps below:

1.To see what life at Capitec is all about and complete a short assessment, pleaseclick here!

2. Once you have completed the above finalize your application by clicking apply below.

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.

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.

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.

The Model Validation team provides assurance on the accuracy, robustness, and governance of models across Capitec. The unit plays a central role in supporting sound risk management, financial decision-making, and regulatory compliance. Our work spans a variety of domains, including credit risk, finance, capital modelling, and fraud detection. The team collaborates closely with modelling and business units, offering technical challenge and validation expertise to ensure models remain fit-for-purpose in an evolving environment.

We are seeking a skilled professional to join our team as a Model Validation Analyst (Decision Science). In this role, you’ll work on end-to-end model validations across different domains, take ownership of key deliverables, and build challenger models to ensure accuracy, reliability, and compliance of the bank’s models

• Proven 3-6 years’ experience in scorecard building, including developing, validating, and monitoring scorecards for credit risk application/behaviour models or marketing purposes. This experience will be used in the role to challenge models presented to the team and to build challenger models.
• Experience with data mining used for analyses and predictive modelling.
• Full understanding of the credit lifecycle.
• Strong analytical ability, with attention to detail and the ability to work across multiple model types.
• A collaborative mindset with the ability to engage effectively across technical and business teams.

• Minimum: Degree in Mathematics , Statistics, Actuarial Science or Data Science.

• Ideal or Preferred: Honours Degree in Data Science , Statistics , Mathematics or Act u arial Science.

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!

• Clear criminal and credit record

Capitec is committed to diversity, applications to this position will strictly be considered in support of our employment equity goals.

Business Segment: Corporate & Investment Banking

Location: ZA, GP, Johannesburg, 5 Simmonds Street

We are seeking an experienced Senior Data Scientist to lead the design, development, and deployment of advanced analytical and machine learning solutions. The ideal candidate will be responsible for solving complex business problems through data-driven insights, predictive modelling, and AI solutions.

This role requires strong expertise in statistical modelling, machine learning, and deep learning, along with proven experience deploying models into production within hybrid cloud environments (Azure and AWS). The Senior Data Scientist will collaborate with stakeholders across business and technology teams, ensuring solutions are scalable, explainable, and deliver measurable value.

Qualifications

Type of Qualification: First Degree
Field of Study:

• Computer Science, Statistics, Applied Mathematics, or related
• Advanced degree (MSc/PhD) preferred.
• Certifications in Azure Machine Learning, AWS Sagemaker, or related platforms advantageous

Experience Required
5-8 years

• Minimum 5–8 years’ experience in Data Science and Machine Learning
• Proven track record of deploying ML models into production (Azure ML, AWS Sagemaker, or Databricks)
• Strong expertise in Python (Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL
• Solid understanding of statistics, time series analysis, NLP, and deep learning
• Experience with MLOps, CI/CD pipelines, and model monitoring
• Exposure to big data ecosystems (Spark, Databricks, Hadoop) is advantageous
• Experience working in financial services or large-scale enterprise environments (preferred)

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Empowering Individuals
• Making Decisions
• Producing Output
• Pursuing Goals
• Resolving Conflict
• Showing Composure
• Upholding Standards
• Machine Learning & Deep Learning (Supervised, Unsupervised, NLP, GenAI)
• Statistical Modelling & Advanced Analytics
• Data Wrangling & Feature Engineering
• MLOps & Model Lifecycle Management
• Business Problem-Solving & Value Creation

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.

The Research Lead will provide scientific and operational leadership for AfriClimate AI’s applied research portfolio, guiding the development, fine-tuning, and validation of AI-driven climate and weather modelling tools. The role involves coordinating a multidisciplinary team, collaborating with African and international partners, and ensuring research outputs are high-quality, open, and impactful.

Research Leadership & Delivery

• Lead the design, implementation, and evaluation of AI-powered, localised climate and weather forecasting methodologies.
• Support the integration of observational data, satellite products, and global reanalysis datasets with AI-based and statistical models.
• Develop benchmarking frameworks for model performance, including bias correction and uncertainty quantification.
• Implement and manage MLOps pipelines for training, deployment, monitoring, and updating AI models in production environments.
• Coordinate cross-functional teams on data collection, model training, and deployment.
• Manage timelines, milestones, and deliverables in line with project objectives.

Stakeholder Engagement and Knowledge Dissemination

Requirements

Essential Qualifications & Experience

Desirable Skills & Experience

Benefits

AfriClimate AI is a grassroots research organisation advancing climate resilience in Africa through open, community-driven AI research. We focus on developing region-specific datasets, tools, and methodologies to bridge the gap between global models and local needs, supporting equitable and actionable climate solutions across the continent.