Head of Data Science

As Head of Data Science, you will define and execute the end-to-end data science strategy — from model research and experimentation through to scalable deployment in live production environments. You will lead a multidisciplinary team of data scientists and ML engineers while partnering closely with Product, Engineering, Risk, and Compliance to ensure solutions are commercially effective, technically robust, and aligned with regulatory expectations. This is both a strategic and hands‑on leadership position within a high‑growth, innovation‑led environment. Key Responsibilities: • Define and execute the data science vision, strategy, and roadmap • Build, lead, and mentor a high-performing team of data scientists and ML engineers • Oversee the design, development, and deployment of advanced ML models across risk, fraud, forecasting, and segmentation • Ensure production‑grade model implementation, monitoring, and optimisation • Partner closely with Product and Engineering to embed models into business systems • Collaborate with Risk and Compliance teams to ensure regulatory alignment, fairness, and explainability • Establish best practices in data governance, feature engineering, experimentation, and MLOps • Define performance metrics to measure business impact of data initiatives • Champion a culture of innovation, experimentation, and continuous improvement Job Experience and Skills Required: Experience: • 10+ years’ experience in Data Science and Machine Learning • Minimum 3 years in a senior leadership or team management role • Proven experience within regulated financial services (e.g., credit, lending, fraud, risk) • Demonstrated success delivering and deploying ML models at scale • Experience working in high‑growth or scaling technology environments advantageous Education: • Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative field (preferred) • Bachelor’s degree in a quantitative discipline required Technical Skills: • Strong programming capability in Python (R or Scala advantageous) • Deep knowledge of supervised and unsupervised learning, statistical modelling, and deep learning • Experience with modern ML frameworks and libraries • Strong SQL and data querying capability • Experience with distributed data processing tools and cloud platforms • Understanding of model governance, explainable AI, and responsible AI principles Core Competencies: • Strategic thinking with strong commercial acumen • Excellent stakeholder communication and executive presentation skills • Strong analytical and problem-solving ability • High attention to detail and commitment to data quality • Ability to operate effectively in a fast‑paced, evolving environment

Cape‑town based and Fully Remote.

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