43 Algorithm Development jobs in South Africa

Calling all AI explorers! Join a cutting-edge lab where your GenAI models shape the future.

From LLMs to data pipelines, you’ll help build intelligence that evolves .

A leading tech-driven organisation is seeking a Generative AI/Data Science specialist to join their innovation lab. This role involves deep AI model development and strong data engineering fundamentals. You’ll focus on building and refining LLM-powered solutions , emphasizing RAG (Retrieval Augmented Generation) frameworks using tools like LangChain and LlamaIndex .

You will partner with data engineers to ensure clean, scalable data pipelines , work on ETL processes and dimensional models, and deploy AI models into live environments with performance and scalability in mind. Additionally, you’ll experiment with new GenAI techniques, support MLOps efforts, and communicate findings to both technical and non-technical stakeholders.

Skills & Experience:

• 3+ years’ experience in AI/ML, with at least 1–2 years specifically in Generative AI
• Proficiency with Python , SQL , and libraries like Pandas and NumPy
• Practical experience with LangChain , LlamaIndex , or other LLM ecosystems
• Strong background in ETL , data engineering , and dimensional modelling
• Experience working across cloud platforms (AWS, Azure, or GCP)
• Familiarity with Docker , Kubernetes , and model deployment best practices
• Exposure to vector databases , Spark , or Hadoop is advantageous
• Confident communicator who can translate complex AI concepts into actionable insights

Qualifications:

• Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or related fields
• Preferred certifications (not required but advantageous):
• AWS Certified Machine Learning / AI Practitioner
• GCP Professional ML Engineer / Associate Cloud Engineer
• Microsoft Azure AI Engineer / Data Scientist

If you’re ready to join a team where innovation thrives and your AI models will thrive , get in touch for a confidential chat.

Because in this world, it’s not about surviving the data jungle—it’s about engineering the future of intelligence .

Contact Kauthar Marcus at or , quoting the Ref: CTI005560 .

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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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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.
  
  

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Department: Sales and Delivery Team - Empower

Industry: Information Technology & Services, Computer Software, Management Consulting

Location: South Africa

Experience Range :8+ years

Basic Qualification: Master/Bachelor of Engineering or Equivalent

Travel Requirements: Not required

Website :

Exusia, a cutting-edge digital transformation company, seeks a Data Scientist to join our global delivery team's Data Engineering & Analytics practice around the world.

What’s the Role?

The Data Scientist role will be part of our Data Engineering & Analytics practice and will be focused on delivering best of breed solutions to our clients leveraging Advanced Analytics & Machine Learning tools and techniques.The candidate will also be part of the practice team and contribute to Competency development, driving innovation through various internal initiatives within the company. Candidate should have more than 8 years of experience with broad exposure to Data Engineering, Data Mining, Business Intelligence & Machine learning

Responsibilities:

• Work on client projects to deliver Data insights using AI, ML and Advanced analytics techniques
• Architect, Build & Deploy scalable Machine Learning models both on premise & on cloud platforms
• Work with the business stakeholders to Identify problem statement, check availability of data and identify appropriate solutions to provide insights to address the problems and deliver better outcomes
• Work closely with the data engineering teams to source and ingest data into data lakes
• Look at semi structured and unstructured data and propose solutions to translate them into structured data format to provide better insights
• Collaborate with S & D leadership to propose and execute ML POCs to deliver quick wins for the clients
• Providing mentorship to junior resources within the data scientist community

Mandatory Skills:

• Should have 6+ years of experience working in Business Intelligence, Analytics and Machine Learning
• Extensive hands-on experience analyzing data with SQL
• Experience in data mining of large data sets using tools like SAS / R / Python to identify patterns
• Experience in using tools like Alteryx or Python libraries like Pandas for preprocessing & cleaning data
• Experience using BI tools like Tableau or PowerBI for self-service analysis and Visualization of data
• Collaborate with data engineering teams to ingest unstructured & semi structured data into data lakes
• Identify data sets, attributes and patterns to propose appropriate ML approach for a given problem
• Strong fundamentals in statistics and its application for building and validating ML models
• Understanding of Supervised, Unsupervised and Reinforcement learning approaches
• Strong experience in using Regression / Classification / Clustering algorithms and their application for appropriate use cases
• Build models using R, Python or Cloud native ML offerings from AWS, AZURE and GCP platforms
• Deploy ML models at scale using tools like TensorFlow Serving, Sagemaker, Torchserve
• Problem-solving skills along with good interpersonal & communication skills

Nice-to-Have Skills

• Exposure to Azure, AWS and Google Cloud Platforms with hands on exposure to ML service offerings
• Experience working with teams located in multiple locations across the globe
• Knowledge and understanding of various Data repositories, Databases, ETL and BI tools and data assets hosted on Hadoop or cloud platforms
• Agile development experience & collaborating with data engineering teams
• Familiarity with Spark, Scala and distributed data processing platforms will be a big advantage
• Ability to work with tools like Jupyter / Databricks notebooks to interactively work with data sets

Exusia, Inc. is committed to maintaining a dynamic work culture. We offer an excellent compensation and benefits package to all employees.

About Exusia:

Exusia ( is a global technology consulting company that empowers its clients to gain a competitive edge by accelerating business outcomes and providing strategy and execution capabilities around digital, analytics and cloud solutions. The company has established its leadership position by solving some of the world's largest and most complex data engineering and analytical problems in the healthcare, financial, telecommunications, consumer products and high technology industries.

Exusia’s mission is to transform the world through the innovative use of information.

Over the past 3 years, Exusia was recognized by Inc. 5000 and by Crain’s publications as one of the fastest growing privately held companies in the world.Since the company’s founding in 2012, Exusia has experienced an impressive seven years of revenue growth and has expanded its operations in the Americas, Asia and Africa. Exusia has recently also been recognized by publications such as the CIO Review, Industry Era, Insight Success and the CIO Bulletin for the company’s innovation in IT Services, the Telecommunications and Healthcare industries and it's entrepreneurship. The company is headquartered in Miami, Florida, United States with development centers in India.

Interested applicants should apply by forwarding their CV to:

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Business Consulting and Services

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City of Johannesburg, Gauteng, South Africa 2 days ago

Johannesburg, Gauteng, South Africa ZAR85,000.00-ZAR110,000.00 6 days ago

Johannesburg, Gauteng, South Africa 1 month ago

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Join to apply for the Head of Data Science role at Di O Rara Personnel

2 weeks ago Be among the first 25 applicants

Join to apply for the Head of Data Science role at Di O Rara Personnel

We have an exciting opportunity for a Head of Advanced Data Science role in an intelligence solutions company. Our client provides services and technologies to help organizations collect, analyze, and utilize data to gain insights and make better decisions. They are looking to hire an experienced candidate who will play an important role in shaping the future of their data science and AI strategy. The successful candidate’s work will be the cornerstone of innovation, transforming complex data into actionable insights that drive significant business impact for clients across various industries. This is more than just a leadership position; it’s an opportunity to pioneer the next generation of predictive and prescriptive analytics solutions.

Requirements

Qualifications: BCom/BSc Honors/MCom/MSc/PhD Statistics, Mathematics or computer science (must have proven machine learning building experience)

Experience: 10 years or more relevant analytical experience with at least 3 in ML/AI

Technical Skills

• Data Analysis: Exceptional ability to work with, analyse, interpret, and develop insights products on data.
• Machine Learning: Strong understanding and practical application of statistical concepts and machine learning techniques.
• Technical Proficiency: Expertise in Python, R & SQL required with experience in TensorFlow, Hugging Face, FastHTML, FastAPI, Flask and Django advantageous.
• Familiarity with Docker containers and predictive model deployment in Microsoft Azure or similar.
• Working with virtualised applications and programming environments.
• Adaptability: Ability to adjust to different programming environments based on the project needs.
• Professional approach to report writing, documentation and other written communications.
• Familiarity with Agile concepts and their application in a Data Science environment.
  
  

• Seniority level Director

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Human Resources Services

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About the Role
Our client is looking for a hands-on Data Science & Enablement Lead to execute the organisation’s data vision and priorities. This role focuses on operationalising Master Data Management (MDM), data governance, data quality, architecture, and enabling AI, advanced analytics, and data science. You will ensure that enterprise data is accurate, governed, and integrated to support business operations, compliance, and innovation. This includes collaborating across Architecture, Operations, Risk, Governance, and IT to build a scalable, science-ready data ecosystem, integrating data from systems such as Oracle E-Business Suite.

Key Responsibilities

1. Enterprise Data Execution
   • Execute enterprise data strategy aligned with transformation, compliance, and AI/data science goals.
   • Champion data standards, governance processes, and quality metrics across functions.
   • Lead governance forums and implement policies, standards, and procedures.
   • Develop and maintain an enterprise data platform using Microsoft Azure, Microsoft Fabric, or similar.
   • Enable business teams with structured, accessible, and trusted datasets.
2. Master Data Management (MDM)
   • Implement MDM framework across master data domains (items, customers, suppliers, etc.).
   • Harmonize master data for consistency across systems and support analytics/AI.
   • Monitor and improve data quality in terms of completeness, accuracy, and timeliness.
3. Data Integration & Platform Development
   • Design and operate a central data lake according to best practices.
   • Lead data integration from systems, including Oracle E-Business Suite and others.
   • Design and implement secure data access controls using Active Directory groups, ensuring authorised data access.
   • Ensure data is accessible, secure, classified, and ready for AI, analytics, and data science.
4. Governance, Stewardship & Quality
   • Implement data ownership, stewardship, and accountability models.
   • Support stakeholders in compliance with governance controls.
   • Monitor data quality metrics and address issues within SLAs.
   • Ensure data meets ethical standards and is suitable for automated and algorithmic use.
5. Cross-Functional Delivery
   • Collaborate with Operations, Supply Chain, and Data Science teams to deliver integrated, reliable data.
   • Work with Risk & Governance teams to maintain compliance, audit, and AI-risk policies.
   • Enable analytics and data science by supporting structured, interoperable data pipelines.

Key Deliverables

• Secure & Scalable Data Lake: Implement and maintain a centralized repository for business-critical data with AD/role-based access.
• Integrated Data Pipelines: Implement reliable and secure pipelines from Oracle and other platforms.
• MDM Framework: Deploy MDM for critical entities (customers, products, vendors) to ensure data accuracy and consistency.
• AI/ML Enablement: Support the design and deployment of ML models for predictive analytics, anomaly detection, segmentation.
• Data Access Architecture: Implement security frameworks based on Active Directory and role-based security.
• AI Infrastructure & Insights: Build infrastructure for model deployment, performance monitoring, and automated reporting.
• Team Collaboration: Lead efforts with business units to discover AI/data opportunities and refine models.

Qualifications & Experience

Essential

• 8–10+ years in data management, including MDM, governance, integration, and quality initiatives.
• Experience in the full development lifecycle of a Data Lake in a mid to large enterprise.
• Expertise in Oracle E-Business Suite and integrating data from multiple systems.
• Deep knowledge of MDM best practices and AI/ML model building.
• Experience with Microsoft Azure, Microsoft Fabric, or similar platforms.
• Strong project management skills for complex data initiatives.
• Proficiency in Python, SQL, Spark, cloud ETL, and orchestration tools.
• Experience in designing secure AD/role-based access control systems.
• Experience with streaming data integration tools like Apache Kafka or Azure Event Hubs.

Desirable

• Familiarity with data governance frameworks (e.g., DAMA, DCAM).
• Experience with data cataloging/metadata tools.
• Experience in regulated industries such as finance, healthcare, or manufacturing.
• Background in FMCG, manufacturing, retail, or other data-intensive sectors.

Education

• Bachelor's degree in IT, Computer Science, Data Science, or a related field.
• Postgraduate qualifications in data, analytics, or BI are advantageous.

Technical Competence

• Skilled in Azure Data Factory, Synapse, Purview, Microsoft Fabric, etc.
• Familiar with Oracle EBS data structures and integration approaches.
• Hands-on experience with MDM tools, ETL platforms, and governance frameworks.
• Strong knowledge of AI/data science needs: labeling, versioning, ethics.
• Proficient in operationalizing analytics pipelines for BI, AI, and ML.
• Experienced with AD-based security and role-based access control.
• Skilled in real-time data streaming solutions (e.g., Kafka, Event Hubs).

Key Competencies

• Strategic thinking and end-to-end solution ownership.
• Strong analytical and problem-solving capability.
• Excellent communication and stakeholder engagement skills.
• Leadership and mentorship abilities.
• Results-driven with a strong focus on quality and delivery.

Job Purpose:

To support the business in identifying opportunities for different segments, and work to use identified insights to design compelling, disruptive and commercially viable Client Value Propositions for the company Insurance offerings.

Job Responsibilities:

• Provide input on activities for relevant CX reports by collecting information on status and results.
• Co-ordinate tasks, resources and internal and external stakeholders to support the implementation of strategic objectives.
• Meet financial objectives by co-ordinating activities in line with budget/target requirements.
• Design and Develop Client Value Proposition (CVP) by ensuring that the CVP’s resonate with the customers’ needs and while aligning with commercial imperatives.
• Identify and engage with all stakeholders to ensure implementation of CVP activities.
• Build and maintain collaborative relationships with stakeholders to deliver on CVP objectives.
• Understand customer needs and market trends.
• Design and develop market leading customer value propositions that are based on customer needs, behaviour, and potential to optimize both customer value proposition and customer experience across our target segments and population groups.
• Ensure that the CVPs resonate with the customers’ needs and also with commercial imperatives.
• Monitor, analyse and articulate in detail competitor activity and emerging market trends to inform the CVPs and ensure the designs remain competitive and up to date.
• Leverage Analytics, MI & Customer Experience to build a fact-based understanding of customer needs and use these insights to support or disprove particular areas of prioritization, focus and courses of action.
• Ensure alignment with the segment customer value proposition.
• Monitor and provide feedback to enhance customer value proposition.
• Contribute to Segment and Proposition strategy.
• Lead and ensure the implementation of the CVP from end to end.
• Generate concise business plans in support of the CVPs.
• Work collaboratively with downstream colleagues with responsibility for building elements of the CVP to a definitive timetable.
• Contribute to a culture conducive to the achievement of transformation goals by participating in the company’s culture building initiatives (e.g. staff surveys, etc.).
• Participate and support corporate social responsibility initiatives for the achievement of key business strategies.
• Identify and recommend opportunities to enhance processes, systems and policies and support implementation of new processes, policies and systems.
• Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.
• Ensure personal growth and enable effectiveness in performance of roles and responsibilities by ensuring all learning activities are completed, experience practiced and certification obtained and/or maintained within specified time frames.
• Ensure information is provided correctly to stakeholders by maintaining knowledge sharing with the team.

Essential Qualifications:

• Advanced Diplomas/National 1st Degrees

Preferred Qualification:

• Post Graduate Diploma: Marketing Management

Type of Exposure:

• Conducting root cause analysis
• Analysing situations or data that requires an in-depth evaluation of multiple factors
• Influencing stakeholders to obtain buy-in for concepts and ideas.
• Challenging the status quo with a view to improving the environment or people's understanding
• Communicating standards to others
• Working with a group to identify alternative solutions to a problem
• Interacting with diverse people

Minimum Experience:

• Overall 7 years + experience in Client Experience, Customer Value Propositions and Customer Insights.
• 5 years’ experience in developing, implementing and being accountable for crafting of CVP, take to market strategy and business plan.
• 6 years’ experience in roles within market insights, consumer research or product management.
• 4 years’ + experience in Insurance and/or financial service industry.

Technical / Professional Knowledge:

• Business terms and definitions
• Cluster specific operations
• Communication Strategies
• Governance, Risk and Controls
• Principles of financial management
• Principles of project management
• Research methodology
• Decision-making process
• Data and Business analysis
• Competitive Intelligence

Behavioural Competencies:

• Continuous Learning
• Customer Focus
• Work Standards
• Building partnerships
• Planning and Organizing
• Technical/Professional Knowledge and Skills

Join to apply for the Chapter Lead: Data Science role at The HEINEKEN Company

Join to apply for the Chapter Lead: Data Science role at The HEINEKEN Company

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Immediate Superior: AME Analyticfs Hub Lead

Location: Johannesburg

Function: Digital & Technology

Sub Function: Digital & Technology - Other Support

Type of Contract: Permanent

Reference Number: 142065

Closing Date: 15/08/2025

The Africa & Middle East (AME) Analytics Hub is a business-led, value-driven satellite of HEINEKEN’s Global Analytics team. Our mission is to help HEINEKEN become the most connected and data-driven brewer in the world.

As part of our continued growth, we are expanding our capabilities and looking for a Data Science Chapter Lead to shape and drive the data science vision for the region. This is a high-impact leadership role where you’ll help define the future of data science across the AME region and contribute to HEINEKEN’s global transformation.

We’re Looking For Someone Who Is

• People-first: You lead with empathy, foster inclusive collaboration, and support the growth of diverse teams.
• Solution-oriented: You bring a pragmatic mindset and a high-degree of ownership and passion for solving real-world business challenges.
• Collaborative by nature: You thrive in cross-functional environments and enjoy working across domains and cultures.
• Strategic and hands-on: You can set a vision, build roadmaps, and also dive into the details when needed.
  
  

• Lead and deliver end-to-end data science solutions that create measurable business value.
• Collaborate across levels and functions—from country teams to regional and global stakeholders in commercial, supply chain, and analytics—to identify pain points, frame problems, and co-create data-driven solutions.
• Champion implementation through effective change management, ensuring adoption and long-term impact.
• Promote engineering excellence by embedding best practices such as CI/CD, modular design, and rigorous testing.
• Design and interpret experiments, including A/B tests and observational studies, translating insights into scalable machine learning solutions.
• Mentor and coach data scientists, fostering a culture of inclusion, psychological safety, and agile ways of working.
  
  

• A seasoned data science leader with expertise in ML engineering, experimentation, and causal inference.
• A strategic thinker who translates business priorities into actionable roadmaps across AME.
• A hands-on engineer, fluent in Python, PySpark, and SQL, with experience in modular ML pipelines (e.g., Databricks).
• A clear communicator, able to engage both technical and non-technical audiences.
• Comfortable with ambiguity and scale, navigating complex data and shifting priorities.
• Passionate about talent, investing in coaching and team growth.
• Bonus: Experience in FMCG, economics/econometrics, and Databricks production deployments.
  
  

• Global opportunities: Work on diverse projects with career paths across countries and regions.
• Continuous learning: Dedicated time for development through workshops, community sessions, and certifications (Microsoft, Databricks).
• A passionate team: Entrepreneurial, driven, and fun—inside and outside of work.
• Hybrid flexibility: Team members are based in Johannesburg, Cape Town
• Meaningful impact: Tackle real challenges and see the results of your work.
• Competitive rewards: Including salary, retirement benefits, and great social events.
  
  

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• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Food and Beverage Services

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