645 Machine Learning Specialist jobs in South Africa

Staff Research Scientist (Machine Learning Specialist) - SDL6

Date Posted: 09/02/2025
Req ID: 45033
Faculty/Division: Faculty of Arts & Science
Department: Acceleration Consortium
Campus: St. George (Downtown Toronto)

Description:

The Acceleration Consortium (AC) at the University of Toronto (U of T) is leading a transformative shift in scientific discovery that will accelerate technology development and commercialization. The AC is a global community of academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also called materials acceleration platforms (MAPs). These autonomous labs rapidly design materials and molecules needed for a sustainable, healthy, and resilient future, with applications ranging from renewable energy and consumer electronics to drugs. AC Staff Research Scientists will advance the field of AI-driven autonomous discovery and develop the materials and molecules required to address society’s largest challenges, such as climate change, water pollution, and future pandemics.

The Acceleration Consortium (AC) promotes an inclusive research environment and supports the EDI priorities of the unit.

The Acceleration Consortium received a $200M Canadian First Research Excellence Grant for seven years to develop self-driving labs for chemistry and materials, the largest ever grant to a Canadian University. This grant will provide the AC with seven years of funding to execute its vision.

The AC is developing seven advanced SDLs plus an AI and Automation lab:

• SDL1 - Inorganic solid-state compounds for advanced materials and energy
• SDL2 - Organic small molecules for sustainability and health
• SDL3 - Medicinal chemistry for improving small molecule drug candidates
• SDL4 - Polymers for materials science and biological applications
• SDL5 - Formulations for pharmaceuticals, consumer products, and coatings
• SDL6 - Biocompatibility with organoids / organ-on-a-chip
• SDL7 - Synthetic scale-up of materials and molecules (University of British Columbia partner lab)
• A central AI and Automation lab to support all the SDLs

Position Overview:

We are seeking a motivated and skilled researcher to join the Acceleration Consortium working with the Human Organ Mimicry SDL. The Self-Driving Lab (SDL) focused on Human Organ Mimicry (HOM) embodies an autonomous artificial intelligence (AI)-assisted platform for culturing and screening high-fidelity models of functional tissues and diseases. In addition to fundamental capabilities like cell passaging and sample preparation, the platform will facilitate closed-loop optimization campaigns designed to optimize cell culture conditions (e.g., growth media and extracellular matrix support), automated generation of model-specific datasets and production of highly reproducible batches of cells with specific phenotypes (e.g., patient-derived organoids (PDOs) and differentiated iPSCs), and development of advanced automated workflows and AI tools (e.g., static and dynamic co-culture organ-on-a-chip (OOC) models, colony picking and bioprinting).

The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or experience to apply those skills toward imaging data (e.g., live cell microscopy). The successful candidate will contribute to advancing machine learning-driven analysis of high-content imaging data to achieve 1) better OOC tissue model functional evaluation and clinical benchmarking, 2) optimization on cost-efficient workflow and reproducibility. The candidate must have knowledge of current machine learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred. Strong coding skills in Python or a comparable programming language are expected, with the ability to develop analysis pipelines and tools that meet project deadlines and are suitable for publication-quality research. The role will involve developing novel computational approaches for biological discovery and working collaboratively in an interdisciplinary research environment. Additional expertise related to biological knowledge of the wet lab experimentation required to gather imaging data is an optional benefit.

This posted position is for a Staff Research Scientist at SDL6 (Human Organ Mimicry).

This is a two-year term with the possibility of renewal.

Expertise that is desired:

Computational expertise

• Life science and physical science applications of machine learning in biology, bioengineering or molecular biology or any other relevant fields.
• Programming and high-performance computing
• Experience in design of computational pipelines for large-scale imaging
• Experience with programming languages and scripting methods (i.e. Python, MATLAB, C++, CUDA, Bash, and/or SQL) and machine learning / deep learning methods
• Active learning, exploration, optimal experiment design, Bayesian optimization, reinforcement learning, and/or representation learning
• Experience in development and application of machine learning/deep learning methods for high throughput cell imaging data

Additional expertise that is desired (but not required):

• Experience with ML-based tools for image-analysis and signal processing, development of ML prediction tools
• Experience with PyTorch and/or TensorFlow, experience with databases and high-content imaging platforms
• Familiarity with generative modeling
• Experience with advanced ML techniques for representation learning and multi-modal data integration

The Staff Research Scientist will work with a diverse team of leading experts at U of T, including Professors Alán Aspuru-Guzik, Anatole von Lilienfeld, Florian Shkurti, Animesh Garg, Oleksandr Voznyy, Robert Batey, Cheryl Arrowsmith, Milica Radisic, and Vuk Stambolic. The Staff Research Scientist will also work with Staff Scientists in Human Organ Mimicry and AI SDL.

The Staff Research Scientists involved in the AC are highly skilled and experienced researchers who will work independently to develop the AI and automation technologies required to build robust and scalable self-driving labs, manage these SDLs, and design and implement research programs (based on the direction of the AC’s scientific leadership team) that leverage the SDL platforms to discover materials and molecules. Moreover, the Staff Research Scientists will work collectively, sharing knowledge among each other, faculty, and trainees. This role will report to the Academic Director and Executive Director of the Acceleration Consortium.

The components and duties of the work can include:

• Machine learning for SDL Development

Working with the AC community, including faculty and partners, this candidate will align computational methods with experimental workflows. The focus will be on developing advanced machine learning algorithms for monitoring various in vitro cell culture models (2D, 3D, organoids and OOCs), as well as enabling data-driven autonomous experimentation. Developing computational tools for the analysis of high-resolution microscopy images of complex tissue models and extracting biologically meaningful insights to support quality control and autonomous decision-making.

• SDL and Automation Development

Working with the AC community, including faculty and partners, determine the required capabilities of the SDLs to be built. Design and testing of closed-loop optimization campaigns for cell culture media optimization using the selected framework. Developing SDL plans to meet user requirements and designing novel instruments for autonomous cell culture experiments. Developing customized hardware and Python software packages to build SDLs. Selecting, procurement, and installation of the equipment required for SDLs.

• Research Direction

Working independently to develop research programs that leverage the AC’s SDLs and supports the research objectives of academic and industrial partners. Translating computational approaches ranging from 2D cell culture models to more complex 3D systems (i.e. organoids and OOCs), with the goal of creating advanced biomimetic models that closely replicate human organ functions and produce clinically relevant data. Preparing and publishing high-quality research manuscripts and contributing to grant writing efforts.

Tasks include:

• Managing the research and development projects of AC’s industry partners when implemented in AC labs
• Developing plans supporting research collaborations and estimating financial resources required for programs and/or projects
• Working with Product Managers to ensure research outcomes meet partner requirements
• Promoting AC’s research capacity, including delivering presentations at conferences
• Collaboration in preparing and submitting research proposals to granting agencies and progress reporting
• Preparing manuscripts for submission to peer review publications/journals and stewarding them through the process
• Mentor junior lab members and promote a collaborative team environment

Other

• Supporting consulting services related to the application of SDLs for materials discovery for the AC’s partners
• Support research-focused events such as Annual Symposium

MINIMUM QUALIFICATIONS:

Education – Ph.D. in computational biology, bioinformatics, biophysics, biomedical engineering, computer science, or a related field.

Experience

• One (1) to 5 years of experience (inclusive of PhD and/or post-graduate work) in accelerated research and development in the area of development and application of machine learning/deep learning methods for biological or chemical data analysis
• Experience working closely with a Principal Investigator or as a Principal Investigator or as Project Director with responsibilities of managing, developing and executing a major research project in the area of AI, machine learning, and/or advanced computational analysis and modeling of biological phenomena
• Experience with overseeing the activities of a lab.
• Experience working with industry partners and on industry led research and development projects.
• Strong experience presenting research at academic conferences.
• Demonstrated record of academic and/or research excellence
• Must have a strong scholarly publication record.

Skills

• Skills in electronic/hardware-oriented programming and machine learning
• Strong and effective communicator in oral and written English
• Collegial in working with team members and collaborators.
• Ability to work independently.

Other

• Demonstrated success in writing and preparing manuscripts, presentations, reports, briefs, and scientific abstracts, and manuscripts for peer-reviewed journals

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority

Closing Date: 10/31/2025, 11:59PM ET
Employee Group: Research Associate
Appointment Type: Grant - Term (2 years term with possibility of renewal)
Schedule: Full-Time
Pay Scale Group & Hiring Zone: R01 -- Research Associates (Limited Term): $3,520 - 100,350 (salary will be assessed and may go above the range based on skills and experience)
Job Category: Research Administration & Teaching

Diversity Statement

The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.

Accessibility Statement

The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission. The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities. If you require any accommodations at any point during the application and hiring process, please contact

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

Referrals increase your chances of interviewing at Beauparc by 2x

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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

Get notified about new Lecturer jobs in United States .

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