Explore exciting Data Science Manager job opportunities in 43 Data Science Manager jobs in Johannesburg
Data Science Manager: Telemetry Solutions
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Who are we?
We made Miway to change the way insurance works, to make it work your way, protecting what matters to you and making life a whole lot easier.
Why Miway?We know what it's like to be in an early morning accident on the way to work, to watch helplessly as water floods your business premises, or have your most precious possessions stolen, to lose a truckload of costly stock, or be stranded a long way from home.
So, we created products that put you first, that help you get back on your feet, that make a difference when you're down and dealing with a loss. That's insurance the way it should be. Insurance your way.
That's Miway.You may want to be part of that. Insurance the way it should be. Built around you.It's about you - not about us.
Why Join Us?
This is a rare opportunity to lead at the frontier of actuarial innovation - where data science, machine learning, and software engineering create real-world impact. As Data Science Manager: Telemetry Solutions, you'll help shape the future of insurance.
- Lead actuarial and data science initiatives across telematics, claims, and operational intelligence.
- Work with rich, real-time datasets from connected vehicles and IoT platforms to unlock insights and build predictive systems.
- Collaborate with cross-functional teams - including product, development, and claims - to integrate analytics into key decision-making processes.
- Apply and grow your technical skills across AI, machine learning, and production-grade systems in a dynamic environment.
- Join a forward-looking team that values innovation, ownership, and continuous learning.
If you're technically strong, strategically curious, and passionate about using data science to tackle bold, modern challenges - this is your opportunity to lead the change.
What will you do?
The Data Science Manager: Telemetry Solutions is a future-focused leadership role that bridges actuarial science, data science, machine learning, and engineering. You will lead a multidisciplinary team that leverages telematics and alternative data to deliver intelligent solutions across usage-based insurance (UBI), claims innovation, product development, and dynamic risk assessment.
This role offers a unique opportunity to operate at the intersection of data, strategy, and technology - driving meaningful transformation in how insurance products are developed, risks are understood, and operations are optimised.
Key Responsibilities
- Architect and deploy scalable, real-time systems for ingesting, processing, and analysing high-frequency vehicle sensor and telemetry data.
- Develop and maintain robust APIs and automation tools in Python and C# to support internal platforms and customer-facing applications.
- Oversee the creation and deployment of AI models - including computer vision and large language models (LLMs) - to enhance claims automation and document intelligence.
- Champion innovation within the actuarial domain by blending traditional methodologies with modern MLOps, software engineering, and streaming analytics.
- Manage end-to-end machine learning pipelines using tools like MLflow, ensuring reproducibility, governance, and performance monitoring.
- Collaborate closely with Product, IT, Data Engineering, and Claims teams to embed intelligent analytics into core business processes and customer experiences.
- Mentor and grow a high-performing team of data scientists, and software engineers.
- Provide technical insight and data-driven narratives to support strategic decision-making through dashboards, models, and actuarial reporting.
Qualifications
- Degree in Actuarial Science, Data Science, Statistics, Computer Science, or a related field (Honours or Master's preferred).
Experience
- Minimum of 5 years' experience in data science, or data engineering roles, preferably in a telematics-driven insurance environment.
- Proficient in Python and C#, with a solid foundation in object-oriented programming and API development.
- Advanced SQL skills, including data processing, database management, and query optimisation (Essential).
- Practical experience using Git for version control and collaboration(Essential).
- Hands-on experience with machine learning libraries and frameworks such as XGBoost, spaCy, Hugging Face, TensorFlow, or PyTorch.
- Proven ability to deploy and monitor models using MLflow and related MLOps tools.
- Experience with large-scale datasets, ideally from IoT or telematics sources.
- Working knowledge of Docker for containerisation (Intermediate to Advanced – Advantageous).
- Exposure to messaging systems such as RabbitMQ (Advantageous).
- Strong understanding of software engineering principles, including object-oriented design and clean code practices.
- Solid business acumen with the ability to translate technical work into strategic outcomes.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Demonstrated leadership experience and a passion for mentoring cross- functional teams.
- Strong analytical and problem-solving skills, with the ability to extract insights from high-volume, high-dimensional data
Knowledge And Skills
Actuarial Problem Solving
Issues management
Business knowledge
Business analysis
Personal Attributes
Self-development - Contributing independently
Interpersonal savvy - Contributing independently
Nimble learning - Contributing independently
Tech savvy - Contributing independently
Core Competencies
Cultivates innovation - Contributing independently
Customer focus - Contributing independently
Drives results - Contributing independently
Collaborates - Contributing independently
Being resilient - Contributing independently
Build a successful career with us
We're all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development and of achieving great things. We pride ourselves in helping our employees to realise their worth. Through its five business clusters – Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office – the group provides many opportunities for growth and development.
Turnaround time
The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers.
Deadline to apply: 19 September 2025.
Our commitment to transformation
At MiWay we believe in cultivating a positive and dynamic working environment that gives you freedom and opportunity to succeed. MiWay is committed to transformation and embracing diversity. This is what drives us to achieve a multicultural workplace with employment equity as a key goal to create an inclusive workforce, reflective of the demographics of our society.
Machine Learning
Posted 25 days ago
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A specialised AI consulting firm is seeking a Machine Learning Engineer to join our team. This role offers the opportunity to work on high-impact AI initiatives within the banking sector , where you will play a key part in designing, deploying, and scaling advanced machine learning solutions. You’ll collaborate with data scientists, engineers, and business stakeholders to deliver end-to-end AI systems that enhance decision-making, improve customer experiences, and optimise critical processes. Beyond building models, you’ll be responsible for ensuring their performance, reliability, and scalability in production—using modern cloud platforms and MLOps practices.
Responsibilities:
- Design, build, and optimise machine learning models for banking applications.
- Implement scalable ML pipelines and integrate them into production environments.
- Collaborate with data scientists, data engineers, and business stakeholders to deliver end-to-end AI solutions.
- Deploy, monitor, and maintain ML models in AWS environments .
- Ensure model reliability, reproducibility, and performance throughout the lifecycle.
- Document methodologies, workflows, and best practices.
Qualifications and experience:
- 3–5 years of experience in machine learning, data science, or related field.
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with large datasets and SQL/NoSQL databases .
- Essential: Hands-on experience with AWS cloud services (SageMaker, S3, Lambda, EC2, Glue, Redshift).
- Familiarity with MLOps practices and CI/CD for ML pipelines.
- Strong problem-solving ability with a track record of translating business needs into technical solutions.
- Experience in banking or financial services is advantageous, but not required.
- Proven experience taking AI models into production at scale .
- Exposure to containerisation (Docker, Kubernetes).
- Familiarity with ML model monitoring and observability tools.
The reference number for this position is NG60802 which is a contract position in Johannesburg/Cape Town offering a contract rate of R550 to R750 per hour, salary negotiable based on experience. e-mail Nokuthula on or call her for a chat on to discuss this and other opportunities.
Are you ready for a change of scenery? E-Merge IT recruitment is a niche recruitment agency. We offer our candidates options so that we can successfully place the right people with the right companies, in the right roles. Check out the E-Merge IT website for more great positions.
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Manager: AI/ML and Data Science
Posted 11 days ago
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The Manager: AI and Data Science is responsible for leading the bank's AI and Data Science initiatives, driving innovation, and enabling advanced analytics capabilities. This role will oversee data scientists, set the AI strategy, and ensure alignment with business goals.
Key Responsibilities:
- Define and implement the AI strategy aligned with the bank's objectives.
- Manage and mentor a team of data scientists, ensuring high-quality AI/ML model development.
- Oversee the development and deployment of AI/ML solutions for business problems.
- Collaborate with stakeholders to identify opportunities for AI-driven innovation.
- Monitor AI/ML model performance and ensure alignment with ethical and compliance standards.
- Promote data-driven decision-making across the organization.
- Bachelors or Masters degree in Data Science, Machine Learning, Computer Science, or related field.
- 5+ years of experience in AI/ML model development and deployment.
- Strong leadership and team management skills.
- Proficiency in Python, R, and relevant ML frameworks.
- Experience with cloud-based AI solutions (AWS, Azure, or GCP).
AI Machine Learning
Posted 2 days ago
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Join to apply for the AI Machine Learning role at Blue Pearl
Join to apply for the AI Machine Learning role at Blue Pearl
Job Description
Standard Bank is seeking a highly skilled AI and Machine Learning Specialist to join our innovative team. In this role, you will leverage your expertise in artificial intelligence and machine learning to develop and implement cutting-edge solutions that drive business value and enhance customer experiences.
Job Description
Standard Bank is seeking a highly skilled AI and Machine Learning Specialist to join our innovative team. In this role, you will leverage your expertise in artificial intelligence and machine learning to develop and implement cutting-edge solutions that drive business value and enhance customer experiences.
Responsibilities
- Model Development:
- Design, develop, and train machine learning models.
- Implement AI algorithms and frameworks.
- Conduct exploratory data analysis to inform model development.
- Model Deployment and Integration:
- Deploy machine learning models into production environments.
- Integrate models with existing systems and data pipelines.
- Ensure seamless operation of deployed models.
- Data Preparation and Feature Engineering:
- Prepare and clean data for model training and evaluation.
- Perform feature engineering to enhance model performance.
- Implement data preprocessing and transformation pipelines.
- Model Evaluation and Tuning:
- Evaluate model performance using appropriate metrics.
- Tune hyperparameters and optimize model accuracy.
- Conduct A/B testing and validation of models.
- Collaboration and Stakeholder Engagement:
- Work with data scientists, engineers, and business stakeholders to understand requirements.
- Translate business problems into technical solutions.
- Communicate findings and model performance to non-technical stakeholders.
- Research and Innovation:
- Stay updated with the latest advancements in AI and ML.
- Experiment with new algorithms and techniques.
- Propose innovative solutions to business problems.
- Documentation and Reporting:
- Document model development processes and methodologies.
- Create user guides and technical documentation.
- Report on model performance and project progress.
- Machine Learning Models:
- Trained and validated ML models.
- Model deployment scripts and integration guidelines.
- Documentation of model architecture and training processes.
- Data Pipelines:
- Data preprocessing and transformation pipelines.
- Feature engineering scripts.
- Documentation of data preparation steps.
- Performance Reports:
- Model performance metrics and evaluation reports.
- Hyperparameter tuning and optimization logs.
- A/B testing and validation results.
- Technical Documentation:
- User guides for deployed models.
- Technical documentation for model development and deployment.
- Maintenance and monitoring procedures.
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field. Advanced degree (e.g., Master's or PhD) preferred.
Proven experience in developing and deploying machine learning models in a commercial or academic environment.
Proficiency in programming languages such as Python, R, or Java.
Strong understanding of statistical methods and data analysis techniques.
Excellent communication skills with the ability to collaborate effectively with technical and non-technical stakeholders.
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- Seniority level Entry level
- Employment type Full-time
- Job function Engineering and Information Technology
- Industries IT Services and IT Consulting
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#J-18808-LjbffrMachine learning engineer
Posted 17 days ago
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We are looking for a talented Machine Learning Engineer to join our team, responsible for developing and deploying machine learning models and algorithms that drive business growth and innovation. The successful candidate will have a strong background in machine learning, deep learning, and software engineering, with a proven track record of delivering high-quality machine learning models and algorithms. The Machine Learning Engineer will work closely with cross-functional teams, including data science, product, and engineering, to identify opportunities for machine learning-driven innovation and develop strategic plans to execute on these opportunities.
Responsibilities:- Design, develop, and deploy machine learning models and algorithms that drive business growth and innovation
- Collaborate with data scientists to develop and implement machine learning models and algorithms
- Work with software engineers to integrate machine learning models and algorithms into production-ready software applications
- Develop and maintain large-scale machine learning systems, including data pipelines, model training, and model serving
- Optimize machine learning models and algorithms for performance, scalability, and reliability
- Stay up-to-date with the latest advancements in machine learning, deep learning, and AI, applying this knowledge to drive innovation and improvement in machine learning models and algorithms
- Collaborate with product managers to develop product roadmaps and prioritize features and requirements
- Develop and maintain relationships with key stakeholders, including business leaders, product managers, and engineering teams
- Communicate complex machine learning concepts and results to non-technical stakeholders, including business leaders and product managers
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
- 3+ years of experience in machine learning, deep learning, or software engineering, with a focus on machine learning model development and deployment
- Strong background in machine learning, deep learning, and software engineering, with expertise in areas such as natural language processing, computer vision, or recommender systems
- Experience with machine learning frameworks and tools, such as TensorFlow, PyTorch, or Scikit-learn
- Strong programming skills in languages such as Python, Java, or C++
- Experience with cloud-based technologies, such as AWS or Google Cloud
- Strong understanding of software engineering principles, including design patterns, testing, and version control
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Technical Skills:
- Machine learning frameworks: TensorFlow, PyTorch, Scikit-learn, etc.
- Deep learning frameworks: Keras, TensorFlow, PyTorch, etc.
- Cloud-based technologies: AWS, Google Cloud, Azure, etc.
Full time
Johannesburg
#J-18808-LjbffrMachine Learning Scientist
Posted 13 days ago
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Youll work with LLMs, RAG frameworks, and scalable data pipelines , collaborate with DevOps and product teams, and be part of a culture that values experimentation, innovation, and continuous learning.
Whats In It For You?:
- Exposure to the latest AI tools and frameworks (LangChain, Llama-Index, and Vector Databases).
- Opportunity to deploy real-world GenAI solutions that drive tangible business outcomes.
- Collaborative, forward-thinking environment where your input shapes strategy.
- Commitment to equity and inclusion African and Coloured candidates are strongly encouraged to apply.
Key Responsibilities:
- Design, implement, and optimize Generative AI solutions and RAG frameworks.
- Develop scalable data pipelines, perform ETL, and design dimensional models for optimal data storage.
- Deploy, monitor, and optimize AI models for performance, scalability, and cost efficiency.
- Collaborate with cross-functional teams to align solutions with business goals.
- Communicate complex AI concepts clearly to non-technical stakeholders.
- Stay ahead of the curve by researching and experimenting with new AI architectures and techniques.
Job Experience and Skills Required:
- Education: Bachelors Degree in Computer Science, Data Science, Machine Learning, or a related field (Masters/PhD preferred).
- Experience: 3+ years in AI/ML, with at least 12 years specialising in Generative AI.
- Technical Skills:
- Proficiency in Python, SQL, Pandas, and NumPy.
- Experience with deep learning frameworks (TensorFlow and PyTorch) and LLM tools (LangChain and Llama-Index).
- Cloud platforms (AWS, GCP, and Azure) and containerization (Docker and Kubernetes).
- Strong data engineering skills (ETL, pipeline design, and data modelling).
- Knowledge of MLOps practices for model versioning, monitoring, and retraining.
- Soft Skills: Proactive, curious, collaborative, and strong communicator.
- Preferred Certifications: AWS ML Specialty, GCP ML Engineer, Azure AI Engineer, or similar.
Apply now!
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Machine learning engineer
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Machine learning engineer
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Senior Machine Learning Developer
Posted 2 days ago
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Position Summary: The Senior Machine Learning Engineer will play a key role in leading the design, development, and deployment of machine learning solutions. You will collaborate with cross-functional teams to identify business opportunities, develop innovative machine learning models, and implement scalable solutions that drive business value. This role offers a unique opportunity to leverage your expertise in machine learning to tackle challenging problems, mentor junior team members, and contribute to the success of our organization.
Key Responsibilities:
- Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
- Collaborate with data scientists, software engineers, and product managers to identify business opportunities and requirements.
- Conduct exploratory data analysis, feature engineering, and model evaluation to ensure robust and reliable performance.
- Implement scalable and efficient machine learning pipelines and workflows to process large volumes of data.
- Stay up-to-date with the latest developments in machine learning research and technologies, and apply them to improve our products and services.
- Mentor and coach junior machine learning engineers, providing guidance, training, and support to develop their technical skills and knowledge.
- Collaborate with cross-functional teams to integrate machine learning models into production systems and applications.
- Document work processes, methodologies, and best practices to facilitate knowledge sharing and collaboration.
Qualifications:
- Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
- 5+ years of experience in machine learning engineering or related roles, with a proven track record of developing and deploying machine learning solutions in production environments.
- Strong proficiency in machine learning algorithms, techniques, and frameworks such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
- Experience with big data technologies and platforms such as Hadoop, Spark, or Apache Flink.
- Proficiency in programming languages such as Python, Java, or Scala.
- Excellent analytical and problem-solving skills, with a strong attention to detail.
- Excellent communication and collaboration skills, with the ability to effectively work with cross-functional teams.
- Demonstrated leadership and mentoring abilities, with a passion for developing and empowering team members.
Machine Learning Data Scientist
Posted 6 days ago
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Key Responsibilities:
- Develop & Enhance AI Models: Create, refine, and implement Generative AI systems and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and Llama-Index.
- Data Engineering: Build scalable data workflows, manage ETL processes, and integrate both structured and unstructured data for AI-driven applications.
- Production Deployment: Deliver models into production, collaborating with DevOps to ensure performance across cloud and on-prem environments.
- Collaborate Across Teams: Work closely with Engineers, product owners, and business leaders to ensure AI solutions drive measurable value.
- Innovate & Research: Stay current with emerging architectures, frameworks, and methodologies, contributing to innovation and thought leadership.
Job Experience and Skills Required:
- Education:
- Degree in Computer Science, Data Science, Machine Learning, or a related field.
- Experience:
- 3+ years of professional experience in AI/ML, including at least 12 years in Generative AI.
- Practical experience with deep learning frameworks (TensorFlow and PyTorch) and generative AI libraries.
- Familiarity with cloud platforms (AWS, GCP, and Azure) and container technologies (Docker and Kubernetes).
- Skills:
- Strong programming ability in Python and SQL, plus experience with libraries like Pandas and NumPy.
- Solid understanding of machine learning algorithms, neural networks, and generative models.
- Knowledge of large-scale data storage (Hadoop, Spark, and Vector databases).
- Understanding of MLOps practices, including model lifecycle management, monitoring, and retraining.
Apply now!
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