Data Scientist position available in Stellenbosch. PBT Group is seeking three experienced Data Scientists (Mid-Level to Senior) to join a high-performing data and analytics team focused on driving credit risk, lending, and business performance decisions through advanced analytics and predictive modelling. This opportunity is ideal for Data Scientists with strong experience in the credit industry, particularly in scorecard development, risk modelling, predictive analytics, and data-driven decision making. Successful candidates will work within a modern cloud-based analytics environment, leveraging Python, SQL, Google Cloud Platform (GCP), BigQuery, and advanced statistical techniques to build and deploy predictive models that support business growth across multiple African markets. The senior-level position requires deep credit risk expertise and proven experience developing and implementing credit scorecards within lending or financial services environments. This is an initial 12-month contract with a strong intention of converting to permanent employment thereafter. Key Responsibilities: Data Science & Predictive Analytics Build, deploy, and maintain predictive models supporting credit risk, customer behaviour, collections, and business optimisation initiatives. Develop, validate, and monitor credit scorecards and risk models. Perform exploratory data analysis to identify trends, patterns, and opportunities within large and complex datasets. Apply statistical modelling, machine learning, and advanced analytical techniques to solve business challenges. Design and implement feature engineering processes to improve model performance and predictive power. Monitor model stability, drift, and performance over time. Credit Risk Analytics Develop and enhance credit risk scorecards and decisioning models. Support lending and credit strategies through data-driven insights and recommendations. Analyse portfolio performance and customer behaviour to improve risk management practices. Collaborate with business stakeholders to translate lending and credit objectives into analytical solutions. Data Analysis & Reporting Extract, transform, and analyse data from multiple sources using SQL and Python. Develop dashboards, reports, and visualisations to communicate insights effectively. Present analytical findings and recommendations to both technical and non-technical stakeholders. Support business performance analysis, customer segmentation, and operational optimisation initiatives. Stakeholder Engagement Collaborate with Data Engineers, Analysts, Product Teams, Credit Teams, and Executive stakeholders. Translate business requirements into analytical frameworks and modelling approaches. Provide guidance and support to business users on data-driven decision-making. Data Governance & Best Practice Ensure compliance with data governance standards, privacy regulations, and internal controls. Maintain documentation relating to models, assumptions, methodologies, and analytical outputs. Contribute to the continuous improvement of analytics methodologies and modelling frameworks. Required Skills & Experience: Essential Experience: 3+ years’ experience (Mid-Level) or 5+ years’ experience (Senior) as a Data Scientist, Credit Risk Analyst, Quantitative Analyst, or similar role. Proven experience developing predictive models within a commercial environment. Strong credit industry experience. Hands‑on experience developing and maintaining credit scorecards. Experience working with large-scale datasets and analytical environments. Technical Skills: Python SQL Data Science & Analytics Predictive Modelling Machine Learning Statistical Analysis Feature Engineering Model Validation Scorecard Development Data Mining Exploratory Data Analysis Cloud & Data Platforms Google Cloud Platform (GCP) BigQuery Google Colab Data Visualisation Looker Studio Power BI (advantageous) Tableau (advantageous) Additional Technologies: Git Jupyter Notebooks Advanced Excel Highly Advantageous Experience: Credit Risk Modelling Retail Lending Consumer Finance Financial Services Banking Collections Analytics Behavioural Scorecards Application Scorecards IFRS9 Exposure Model Governance African lending environments Qualifications Required: Bachelor’s Degree in: Mathematics Statistics Data Science Computer Science Actuarial Science Engineering Related quantitative discipline Preferred Honours or Master’s Degree Advanced Analytics, Machine Learning, or Credit Risk certifications #J-18808-Ljbffr