R&D Machine Learning Analyst

JOB TITLE:  Junior R&D Machine Learning Analyst LOCATION:  Stellenbosch, South Africa About Dynamo We are an international team, passionate about understanding how the world of business-critical modelling is evolving, and we apply our mathematical skills, professional expertise and intelligent automation software to deliver actuarial and financial modelling solutions for our forward-thinking clients.  THE OPPORTUNITY: As a Junior R&D ML Analyst, you will contribute to the development and testing of machine learning and analytical tools that support Dynamo’s consulting and software offerings. You’ll work closely with senior researchers, actuaries, and software engineers to explore new techniques for solving traditional actuarial and finance problems, evaluate model performance, and help translate research into practical applications and software functionality. Key Responsibilities Assist in designing, training, and validating ML algorithms in applications such as loss reserving. Contribute to feature development leveraging GenAI, e.g. RAG or MCP implementations. Support research into new algorithms and ML applications in finance and actuarial. Contribute to the adoption of ML models into Dynamo’s proprietary software platform, Psicle. Participate in team discussions, code reviews, and knowledge-sharing sessions.  Skills, qualifications & experience  Bachelor’s degree in a quantitative field (e.g., Data Science, Computer Science, Statistics, Applied Mathematics). Strong foundation in coding. e.g. Python, C#, F# or Julia Good understanding of a wide range of supervised and unsupervised learning optimisation and modelling techniques. Good communication skills and a collaborative mindset. Curiosity and willingness to learn in a fast-paced R&D environment.  Desirable skills and experience Experience with ML libraries (e.g., scikit-learn, TensorFlow or PyTorch). Masters degree in a statistical learning or machine learning Exposure to actuarial or insurance-related data. Experienced with version control (e.g., Git) and good code practices. Knowledge of model interpretability and explainability techniques. Experience with tools such as LangChain and Azure AI Foundry  How to apply  Recruitment is a two-way process, so we’d love to know why this could be the place for you and what you are looking for to advance your career, even if you do not tick all the boxes. To progress your application, please send your CV and covering letter to careers@dyna-mo.com. If you have questions, please add these to your email, so we can discuss as part of the application/initial conversation.  Dynamo respects the uniqueness of all, if you require any support to help your application shine, or to enable you to do your best through the selection process, please let us know when sending your application so we can do everything reasonable to enable you.  Please refer to our Data Privacy Policy for information on how we treat your data.