Join a growing financial consultancy specialising in sustainable credit and capital solutions. Working alongside industry experts, youll be responsible for building, improving, and transforming predictive and financial models that directly impact business performance. Here, innovation is encouraged, ideas are heard, and your technical expertise will be recognised. This role offers strong exposure to end-to-end modelling, business strategy, and hands-on analytics work ideal for someone who wants more autonomy and impact. Please Note: This role is based in Cape Town, and candidates must have their own reliable transport. Key Responsibilities: Build, enhance, and maintain predictive and financial models used in credit and capital decision-making. Identify underperforming models and optimise or rebuild them for improved accuracy and efficiency. Develop advanced dashboards and data solutions in Qlik to support business insights and reporting. Work with large datasets and translate analytics into practical business recommendations. Collaborate with stakeholders and provide clear analytical insights to support decision-making. Job Experience and Skills Required: BSc / BCom / Honours in Data Science, Actuarial Science, Statistics, Mathematics, or a similar quantitative field. 3 years’ experience in a data analytics, data science, actuarial or quantitative modelling role. Advanced Qlik skills (QlikView / Qlik Sense) essential. Proven experience in building and modifying predictive/financial models . Strong proficiency in SQL, Python or R. Ability to work independently, solve complex problems, and communicate analytical insights. Must reside in Cape Town and have own reliable transport (non-negotiable). Apply now!

Requirements: A degree in Data Science, Statistics, Mathematics, or a related quantitative discipline A minimum of 3 years of experience in Data Science, Risk Analytics, or Credit Risk Management. Experience building and validating credit risk models, including scorecards and provisioning. Proficiency in Databricks, SQL, R, or Python. Familiarity with IFRS 9, Basel, or equivalent credit risk regulatory frameworks. Exposure to cloud-based data platforms (AWS, GCP, Azure). Strong background in statistical modelling, machine learning, and predictive analytics. Knowledge of advanced machine learning techniques and model interpretability methods. Responsibilities: Develop, implement, and maintain acquisition scorecards to evaluate MCA applicants. Monitor provision models aligned with regulatory and accounting standards. Enhance portfolio monitoring tools to track credit performance and early warning signals. Analyse transaction data, repayment patterns, and business health metrics to inform risk strategies. Identify trends, correlations, and anomalies that impact credit performance and portfolio stability. Collaborate with product, finance, and operations teams to embed data-driven decision-making.