📌 OPPORTUNITY OVERVIEWIGrow Wealth Investments is actively recruiting for a Data Scientist position in Western Cape. This is an excellent opportunity for professionals in the Data / Business / Analysis / Ai sector looking to advance their careers.
🎯 IDEAL CANDIDATE PROFILEWe are seeking talented individuals with the following profile• Experience Level: 5 years • Educational Background: Others or equivalent • Industry Focus: Data / Business / Analysis / Ai • Location Preference: in Western Cape
💼 WHY THIS ROLE MATTERSThe Data Scientist position is an important role within the Data / Business / Analysis / Ai sector, offering meaningful career development and professional growth opportunities.
📈 CAREER DEVELOPMENT INSIGHTSThis role in Data / Business / Analysis / Ai offers valuable career progression opportunities aligned with your experience level and professional aspirations.
📋 APPLICATION GUIDANCEWhen applying for this Data Scientist position, ensure your CV highlights: • Relevant experience matching the 5 years requirement • Educational qualifications in line with Others • Specific achievements in the Data / Business / Analysis / Ai field • Any certifications or specialized training
🌍 SOUTH AFRICA JOB MARKET CONTEXTThe Data / Business / Analysis / Ai sector in South Africa continues to show strong demand for skilled professionals. This position represents a valuable opportunity in the current job market.
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IGrow Wealth Investments Group of Companies, proudly positioned as South Africa’s #1 Investment company, is seeking a curious, driven Mid-Level Data Scientist to join our innovative and growing team based in Durbanville, Cape Town. You will work across the full data science lifecycle — from problem framing and exploratory analysis through to model development, deployment, and monitoring. Your work will span machine learning, natural language processing, generative AI, computer vision, and statistical analytics, all delivered on IGrow's Python, PostgreSQL, and Docker stack — directly influencing product decisions and business outcomes.
Minimum requirements (Advantageous):
Postgraduate degree (Honours, Masters, or PhD) in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering. Minimum 5 years of hands-on experience in a data ccience or spplied machine learning role. Strong proficiency in Python for Data Science (NumPy, pandas, scikit-learn, PyTorch or TensorFlow). Solid understanding of machine learning fundamentals, including model selection, cross-validation, regularisation and evaluation metrics. Practical experience with Natural Language Processing (NLP) and Large Language Models (LLMs), including Transformers, BERT and GPT models. Proficiency in SQL and PostgreSQL for data extraction and manipulation. Experience deploying machine learning models using Docker. Strong statistical knowledge, including hypothesis testing, probability, regression and experimental design. Ability to communicate technical concepts effectively to non-technical stakeholders. Practical knowledge of Generative AI tools, including LangChain, LlamaIndex, OpenAI API, Claude and Hugging Face. Ability to build RAG solutions using vector stores such as PostgreSQL/pgvector. Exposure to computer vision frameworks, including OpenCV, torchvision, YOLO and Detectron2. Familiarity with AI automation and development tools, including n8n, Zapier, Base44 and Claude Code. Front-end development skills in React, TypeScript, Tailwind and Framer Motion for building model-facing tools. Knowledge of Zoho CRM integrations using Deluge and JavaScript.
Duties and responsibilities include, but not limited to:
Machine Learning & Predictive Modelling
Design, train, evaluate, and deploy supervised and unsupervised machine learning models in Python. Build predictive and prescriptive models across classification, regression, clustering, and ranking tasks. Own the full ML lifecycle: data preparation, feature engineering, model selection, validation, deployment, and monitoring Package and deploy models in Docker for reproducible, versioned, maintainable production use.
NLP & Generative AI
Develop and fine-tune NLP models for text classification, named entity recognition, sentiment analysis, and summarisation Leverage LLMs and generative AI (Claude, OpenAI API, Hugging Face) to build intelligent applications Design prompt engineering strategies and retrieval-augmented generation (RAG) pipelines using PostgreSQL/pgvector for vector storage. Evaluate and mitigate risks in generative AI outputs including hallucination, bias, and fairness.
Computer Vision
Build and adapt computer vision models for image classification, object detection, and segmentation. Work with pre-trained architectures (e.g. CNNs, ViTs) and fine-tune on domain-specific datasets. Collaborate with engineering teams to integrate vision models into production systems.
Analytics, Dashboards & Statistical Insights
Conduct rigorous exploratory data analysis (EDA) and statistical modelling to surface actionable insights. Design and analyse A/B tests and experiments to measure the impact of product and business changes. Translate complex analytical findings into clear, compelling narratives for non-technical stakeholders. Build dashboards and internal tools using React, TypeScript, Tailwind, and Framer Motion to track model and business KPIs.
AI Automation & Workflow Integration
Use AI developer tools such as Claude Code and LLMs to accelerate experimentation and delivery Automate data and model workflows with n8n, Zapier, and Base44 Integrate model outputs and insights into iGrow systems including Zoho CRM (via Deluge and APIs)
Collaboration & Research
Partner with data engineers to ensure high-quality data is available for modelling. Work with product managers and stakeholders to define problems, success criteria, and evaluation metrics Stay current with research developments in ML, NLP, and AI; evaluate and apply relevant techniques Document methodologies, experiments, and model decisions to support reproducibility and knowledge sharing.
