Senior Data Scientist
Senior Data Scientist
Own end-to-end AI initiatives from problem framing to production deployment for a bespoke AI consultancy.Remote (South Africa), AI Consultancy, R120 000 - R140 000 p/m.
About Our Client
The company is a specialist AI consultancy that partners with leading enterprises, particularly in financial services and other regulated sectors, to design, build, and scale AI solutions. They focus on moving AI from experimentation into production by combining technical expertise with commercial insight and governance awareness across the full AI lifecycle.
The Role: Senior Data ScientistThis role exists to own end-to-end AI initiatives and translate complex business challenges into high-impact use cases. The focus is on working closely with stakeholders and engineering teams to design, build, and deploy robust, explainable, and scalable machine learning solutions within regulated environments.
Key Responsibilities- Possess 7+ years of professional experience in data science, machine learning, or applied AI roles.
- Own end-to-end AI and machine learning initiatives from ideation through to production deployment.
- Translate complex business challenges into clearly defined, high-impact AI use cases.
- Design, build, and evaluate advanced machine learning models including tree-based models, deep learning, and graph-based approaches.
- Collaborate with data engineers and ML engineers to deploy robust, scalable ML pipelines.
- Apply best practices in model validation, explainability, monitoring, and performance management.
- Provide technical leadership and mentorship within cross-functional teams.
- Contribute to responsible AI, governance, and ethical AI practices.
- 7+ years of professional experience in data science, machine learning, or applied AI roles.
- Bachelors degree in Engineering, Computer Science, Data Science, Mathematics, or a related quantitative field.
- Strong proficiency in Python for machine learning and data science.
- Experience delivering production-grade ML solutions with measurable business impact.
- Experience with frameworks such as scikit-learn, XGBoost, TensorFlow, and deep learning techniques.
- Hands-on experience with AWS, including production ML services such as SageMaker.
- Solid grounding in statistics, machine learning theory, and experimental design.
- Strong SQL skills and experience working with large-scale data platforms.
- Masters degree in Machine Learning / Artificial Intelligence or equivalent practical experience.
- Experience delivering ML solutions within financial services or other regulated industries.
- Exposure to MLOps, CI/CD, and model deployment workflows.
- Experience working in Agile or SAFe environments.