222 Deep Learning jobs in South Africa

Beauparc Mogalakwena, Limpopo, South Africa

Join to apply for the Data Science Lead role at Beauparc

Beauparc Mogalakwena, Limpopo, South Africa

Join to apply for the Data Science Lead role at Beauparc

• Manage the delivery of data science solutions from inception, through Proof of Concept and into production, using a range of tools and methods.
• Data Analysis: Collect and analyze data from various sources, including internal systems, third-party tools, and market research.
• Dashboard Implementation and Creation: Oversee the development, implementation, and maintenance of dynamic dashboards to visualize key metrics, enabling stakeholders to monitor performance and make data-driven decisions.
• Key Performance Indicators (KPIs): Define KPIs and develop reports to monitor and measure performance based on these indicators.
• Cross-Department Collaboration: Work alongside IT teams to ensure that data infrastructure, systems, and tools are optimized for efficient collection, storage, and analysis.
• Data Structure and Sources: Play a crucial role in deciding the data structure and determining the most relevant and reliable data sources for business analysis. Ensure data integrity and consistency across all platforms.
• Data Visualization: Create compelling presentations that convey analytical insights and actionable recommendations to senior management and stakeholders.
• Data-Driven Decision Culture: Foster an organizational culture that values and utilizes data-driven decision-making, promoting continuous improvement and innovation.
• Make business recommendations based on the data that drives better business decisions.
  
  

• Manage the delivery of data science solutions from inception, through Proof of Concept and into production, using a range of tools and methods.
• Data Analysis: Collect and analyze data from various sources, including internal systems, third-party tools, and market research.
• Dashboard Implementation and Creation: Oversee the development, implementation, and maintenance of dynamic dashboards to visualize key metrics, enabling stakeholders to monitor performance and make data-driven decisions.
• Key Performance Indicators (KPIs): Define KPIs and develop reports to monitor and measure performance based on these indicators.
• Cross-Department Collaboration: Work alongside IT teams to ensure that data infrastructure, systems, and tools are optimized for efficient collection, storage, and analysis.
• Data Structure and Sources: Play a crucial role in deciding the data structure and determining the most relevant and reliable data sources for business analysis. Ensure data integrity and consistency across all platforms.
• Data Visualization: Create compelling presentations that convey analytical insights and actionable recommendations to senior management and stakeholders.
• Data-Driven Decision Culture: Foster an organizational culture that values and utilizes data-driven decision-making, promoting continuous improvement and innovation.
• Make business recommendations based on the data that drives better business decisions.
  
  

• Education: Bachelor’s degree in Mathematics, Statistics, Computer Science, or a related field.
• Experience: Over 3 years of experience in data analytics
• Technical Skills: Proficiency in data analysis and visualization tools such as SQL, Excel, Tableau, Power BI, or similar. A focus on Power BI experience.
• Dashboard Creation Expertise: Extensive experience in designing and implementing effective dashboards that provide real-time insights and enable the business to track performance and make informed decisions.
• Additional Knowledge: Experience in strategic planning using quantitative techniques, managing large data volumes, and advanced statistical techniques.
• Interpersonal Skills: Excellent communication and presentation skills, with the ability to translate complex data into clear, actionable insights.
• Experience using Data Science algorithms and methods to solve business problems using R or Python
• Excellent capability in SQL to extract data from databases
  
  

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Utilities

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COO (Data Science) position available in Stellenbosch.

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

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THE WORK : Join our dynamic team and embark on a journey where you will be empowered to perform independently and become an SME. Required active participation/contribution in team discussions and contribute in providing solutions to work related problems. Let's create a brighter future together!

Use existing research methods and develop new approaches to discover anthropological, ethnographical and sociological insights.

Develop brand tracking systems and convert data into relevant KPI dashboards.

Utilize analytical methodologies, mathematical modeling or optimization techniques to develop intellectual property.

BONUS POINTS IF YOU HAVE:

• Advanced proficiency in Generative Design
• Advanced proficiency in Machine Learning

HERE'S WHAT YOU WILL NEED:

• Expert proficiency in Data Science.
• Advanced proficiency in Data Analytics.
• A minimum of 1 year of experience in relevant related skills.
• Bachelor's Degree in relevant field of studies

BONUS POINTS IF YOU HAVE:

• Advanced proficiency in Generative Design
• Advanced proficiency in Machine Learning

Kuda is a money app for Africans on a mission to make financial services accessible, affordable and rewarding for every African on the planet.

We're a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love so it's only right that we ended up with the name ‘Kuda' which means ‘love' in Shona, a language spoken in the southern part of Africa.

We're giving Africans around the world a better alternative to traditional finance by delivering money transfers, smart budgeting and instant access to credit through digital devices.

We've raised over $90 million from some of the world's most respected institutional investors, and we're rolling out our game-changing services globally from our offices in Nigeria, South Africa, and the UK.

Role Overview

As the Data Science Manager at Kuda, you will be responsible for leading a dynamic team of data scientists to develop and deploy machine learning models that drive critical business outcomes across the entire credit lifecycle. Your team will focus on building solutions for credit scoring, fraud detection, and collections, while also supporting various other business functions by providing data-driven insights and predictive capabilities.

You will work with cutting-edge technologies in data science and machine learning, with an emphasis on building scalable, real-time decisioning systems that are integrated into our product offerings. This means that your models will not only be developed but also put into production in a way that supports live, real-time decisions, enhancing Kuda's ability to serve customers with speed and precision.

Your role will require collaboration across multiple cross-functional teams, including product, business, technology, and data teams, ensuring that all teams are aligned to deliver value through innovative, data-driven solutions. As a manager, you'll foster an environment of continuous learning and improvement, ensuring that your team stays ahead of the curve in terms of industry trends, emerging technologies, and the most effective methodologies in the field of data science.

Key to your success will be your ability to translate business challenges into data-driven solutions while balancing technical execution with strategic vision. Your leadership will help scale Kuda's impact, bringing high-quality, machine learning-based credit solutions to millions of customers across Nigeria and beyond.

Key Responsibilities

• Team Leadership: Manage and mentor a team of data scientists, fostering a collaborative and innovative environment
• Model Development: Lead the design, development, and deployment of machine learning models for credit scoring, fraud detection, and collections
• Cross-Functional Collaboration: Work closely with product, engineering, and compliance teams to integrate models into production systems
• Data Analysis: Analyze large, complex datasets to extract actionable insights and inform business strategies
• Model Monitoring: Oversee the performance of deployed models, ensuring they meet business objectives and regulatory standards
• Stakeholder Communication: Present findings and recommendations to senior leadership and other stakeholders
• Continuous Improvement: Stay abreast of industry trends and emerging technologies to continuously enhance model performance and team capabilities
  
  

• Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field
• Experience: Minimum of 6 years in data science, with at least 2 years in a leadership role managing teams and projects
• Technical Skills: Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). Strong knowledge of cloud environments and services (AWS, Google Cloud)
• Domain Knowledge: Experience in credit risk modeling, fraud detection, or financial services is highly desirable
• Leadership: Strong ability to lead teams, manage projects, and communicate effectively with both technical and non-technical stakeholders
• Regulatory Awareness: Understanding of financial regulations and compliance standards, particularly in the Nigerian context.
  
  

Kuda is a money app for Africans on a mission to make financial services accessible, affordable and rewarding for every African on the planet.
We’re a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love so it’s only right that we ended up with the name ‘Kuda’ which means ‘love’ in Shona, a language spoken in the southern part of Africa.
We’re giving Africans around the world a better alternative to traditional finance by delivering money transfers, smart budgeting and instant access to credit through digital devices.
We’ve raised over $90 million from some of the world's most respected institutional investors, and we’re rolling out our game-changing services globally from our offices in Nigeria, South Africa, and the UK.

Role Overview

As the Data Science Manager at Kuda, you will be responsible for leading a dynamic team of data scientists to develop and deploy machine learning models that drive critical business outcomes across the entire credit lifecycle. Your team will focus on building solutions for credit scoring, fraud detection, and collections, while also supporting various other business functions by providing data-driven insights and predictive capabilities.

You will work with cutting-edge technologies in data science and machine learning, with an emphasis on building scalable, real-time decisioning systems that are integrated into our product offerings. This means that your models will not only be developed but also put into production in a way that supports live, real-time decisions, enhancing Kuda's ability to serve customers with speed and precision.

Your role will require collaboration across multiple cross-functional teams, including product, business, technology, and data teams, ensuring that all teams are aligned to deliver value through innovative, data-driven solutions. As a manager, you'll foster an environment of continuous learning and improvement, ensuring that your team stays ahead of the curve in terms of industry trends, emerging technologies, and the most effective methodologies in the field of data science.

Key to your success will be your ability to translate business challenges into data-driven solutions while balancing technical execution with strategic vision. Your leadership will help scale Kuda’s impact, bringing high-quality, machine learning-based credit solutions to millions of customers across Nigeria and beyond.

Key Responsibilities

• Team Leadership : Manage and mentor a team of data scientists, fostering a collaborative and innovative environment.
• Model Development : Lead the design, development, and deployment of machine learning models for credit scoring, fraud detection, and collections.
• Cross-Functional Collaboration : Work closely with product, engineering, and compliance teams to integrate models into production systems.
• Data Analysis : Analyze large, complex datasets to extract actionable insights and inform business strategies.
• Model Monitoring: Oversee the performance of deployed models, ensuring they meet business objectives and regulatory standards.
• Stakeholder Communication : Present findings and recommendations to senior leadership and other stakeholders.
• Continuous Improvement : Stay abreast of industry trends and emerging technologies to continuously enhance model performance and team capabilities.

• Education : Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• Experience : Minimum of 6 years in data science, with at least 2 years in a leadership role managing teams and projects.
• Technical Skills : Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). Strong knowledge of cloud environments and services (AWS, Google Cloud).
• Domain Knowledge : Experience in credit risk modeling, fraud detection, or financial services is highly desirable.
• Leadership : Strong ability to lead teams, manage projects, and communicate effectively with both technical and non-technical stakeholders.
• Regulatory Awareness: Understanding of financial regulations and compliance standards, particularly in the Nigerian context.

Why join Kuda?

At Kuda, our people are the heart of our business, so we prioritize your welfare. We offer a wide range of competitive benefits in areas including but not limited to:

A great and upbeat work environment populated by a multinational team

Pension

Career Development & growth

Competitive annual leave plus bank holidays

Competitive paid time off (Parental, Moving day, Birthday, Study leave etc)

Group life insurance

Medical insurance

Well-fare package (Wedding, Compassionate and etc)

Perkbox

️Goalr - employee wellness app

Award winning L&D training

We are advocates of work-life balance, working in a hybrid in office schedule

Kuda is proud to be an equal-opportunity employer. We value diversity and anyone seeking employment at Kuda is considered based on merit, qualifications, competence and talent.

We don’t regard colour, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status. If you have a disability or special need that requires accommodation, please let us know.

Fintech is entering a new phase where operational and commercial excellence has become critical for success. We at MTN believe this is a game changer in terms of our business strategy. We are looking at an incumbent to join us as we build a successful business together.

As part of your portfolio as a
Manager: Data Science
you will:

• Lead the development and implementation of the
  AI and advanced analytics strategy
  , ensuring alignment with MTN Fintech's business objectives.
• Translate business needs into
  AI/ML use cases
  that deliver measurable impact (growth, efficiency, risk mitigation).
• Drive adoption of
  real-time and prescriptive analytics
  , embedding AI into decisioning and product workflows.
• Develop comprehensive implementation plans for data science projects, balancing innovation speed with governance.
• Build frameworks for
  AI readiness assessment
  , ensuring data quality, ethics, and infrastructure alignment.
• Provide analytical insight to shape product, marketing, and risk strategies.
• Foster partnerships with Group Technology and external AI/ML vendors to co-create scalable data solutions.
• Drive delivery of
  end-to-end machine learning pipelines
  from data ingestion to model deployment and lifecycle management.
• Execute
  AI-driven automation
  for fraud detection, customer segmentation, personalization, and pricing optimization.
• Leverage large-scale wallet and transactional data to identify patterns, forecast trends, and optimize risk strategies.
• Apply advanced analytics, including
  deep learning, NLP, computer vision, and graph analytics
  , to solve complex fintech challenges.
• Enable
  MLOps practices
  for model monitoring, retraining, and continuous delivery.
• Collaborate with data engineers to evolve next-generation data platforms (streaming, real-time data lakes).
• Build and scale
  AI-enabled APIs and microservices
  that plug directly into operational and customer-facing platforms.
• Drive
  data democratization
  by developing self-service analytical tools for business teams.
• Explore opportunities for
  data monetization
  through insights-as-a-service and ecosystem partnerships.
• Implement
  Responsible AI principles
  , ensuring fairness, explainability, and transparency across models.

The incumbent
must have
the following:

• Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
• Master's Degree in a Data Science, AI/ML, Statistical or related field (preferred)
• MBA or Masters (advantageous)
• 5 or more years of relevant work experience as a Data Engineer/ Data Scientist
• 4–6 years applied data science; 2+ years owning production AI/ML.
• At least 3 years' experience within a non-traditional FinTech, Banking or Financial Services Sector
• Experience in Data Science and Data Analysis with a specific focus on AI/ ML models within banking, finance and/or telecommunications industry
• Proven delivery of automated decisioning (recommendation/propensity/fraud/forecasting) with quantified business impact.
• Experience in Data Engineering within banking or financial services industry
• Understanding of enterprise-scale systems and technologies used in data infrastructures
• Experience of working in an Agile/DevOps environment
• GitHub or GitLab experience for CI/CD
• Consistent improvement CI/CD applications for collaborations and enhancement to drive develop once and deploy to many mindset through container repositories
• Proficiency in working with Python and its relevant libraries SAS or R / Scala for data clean up and advanced data analytics
• Working knowledge in Hadoop, Apache Spark and related Big Data technologies (MapReduce, PIG, HIVE)
• Demonstrated experience utilizing software tools to query and report data and being software agnostic
• Highly proficient in database management systems like Postgres, Oracle, Mongo, MSSQL
• Experience in data analysis and management, business performance management and/or reporting within the financial sector or banking industry

Ready to make and drive the change with us? Apply now

Closing date: 15 October 2025. Late applications will not be accepted.

Should you not hear from us within 2 weeks of applying, please consider your application unsuccessful.

• 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

Job Overview

As Lead Data Science & DataOps Engineer, you will lead our Data Science and DataOps functions, driving technical excellence, strategic alignment, and innovation across projects, ensuring that best practices and processes are followed, and the quality of data science, data ops and dashboarding solutions are maintained. This role requires deep technical expertise in data science, AI/ML, and data engineering, alongside strong leadership and mentoring capabilities. You will ensure quality delivery, scalable architecture, and ethical use of data while building a high-performing team that supports Reach's strategic priorities.

Key Focus Areas

1. Strategic & Technical Leadership

2. Provide strategic direction and technical leadership across Data Science, AI/ML, and DataOps.

3. Define and drive a roadmap aligned with organisational goals, with a focus on digital health, impact measurement, and large-scale behaviour change.
4. Guide architectural decisions, assess technical risks, and ensure alignment with broader engineering goals.

5. Play an active role in shaping Reach's technology strategy and contribute to organisation-wide KPIs.

6. AI/ML Research & Development

7. Drive the design, development, and deployment of high-impact AI/ML models (e.g. LLMs, predictive modelling, NLP, recommendation engines).

8. Explore and experiment with emerging technologies, algorithms, and tools to push the boundaries of innovation.

9. Champion ethical, responsible AI - ensuring fairness, transparency, and accountability in model design and use.

10. DataOps & Infrastructure

11. Oversee the design, development, and automation of scalable and secure data pipelines, workflows, and infrastructure.

12. Implement data governance, privacy, and compliance standards across data and model operations.

13. Collaborate with SRE, MERL and Engineering teams to ensure seamless integration of data workflows.

14. People Leadership & Team Growth

15. Build, manage, and mentor a high-performing team across Data Science, AI/ML, and DataOps disciplines

16. Promote a culture of learning, knowledge sharing, and psychological safety.

17. Support professional development and growth of individuals and the broader function.

18. Collaboration & Cross-Functional Impact

19. Collaborate with cross-functional teams including MERL, SxD, Engineering, and

20. Implementation to ensure high-quality delivery and impact.
21. Provide data-driven insights and support the development of monitoring tools for real-time evaluation.

22. Support on technical input for proposals, concept notes, and partnership development.

23. Operational Excellence & Ways of Working

24. Champion process improvements, AI/ML and DataOps practices, and reproducibility standards.

25. Promote consistent adoption of best practices across all data and model development workflows.
26. Take responsibility for risks, delivery timelines, and the quality of technical outputs.

Responsibilities

• Lead end-to-end development of AI/ML and data solutions, from ideation to deployment and monitoring.
• Design experiments, perform impact analyses, and contribute to data strategy for research and delivery teams.
• Drive continuous evaluation and improvement of models and pipelines.
• Manage team resourcing, performance, recruitment, and onboarding.
• Represent the team internally and externally through conferences, stakeholder engagements, and publications

Qualifications

• Relevant degree in a quantitative or technical field (e.g. Computer Science, Engineering, Statistics, Mathematics, Economics) or equivalent experience.
• Strong mathematical background and a proven track record in data science, data engineering, or AI/ML senior roles.

Skills & Experience Required:

• 7+ years of relevant experience, including 3+ years in a senior or leadership role.
• Strong expertise in data science, data engineering, and AI/ML development.
• Hands-on experience with cloud platforms (AWS, GCP, Azure), DataOps and MLOps tools (CI/CD pipelines, model monitoring), and orchestration tools.
• Strong coding skills (Python, Bash, etc.) and experience with distributed computing.
• Excellent communication and stakeholder engagement skills.
• Demonstrated ability to lead cross-functional, multidisciplinary teams.

Desirable:

• Experience with big data technologies (Spark, Hadoop), containerisation (Docker, Kubernetes), and open-source contributions.
• Knowledge of data privacy regulations and ethical frameworks for AI.