Data Scientist II - Pricing at FNB South Africa

Job Description

• To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, to address business opportunities and problems and implement business strategy, with minimal guidance.

Role Overview

• We are seeking a strategic and analytically driven Data Scientist II to join our Credit Risk team. This role focuses on using predictive modeling to inform and shape business strategies across the credit lifecycle.
• The successful candidate will work closely with business teams to translate data insights into actionable strategies that drive growth, manage risk, and improve customer outcomes.

Key Responsibilities

• Develop and implement predictive models to support strategic initiatives such as: Risk-based pricing of loans; Profitability modeling; Risk appetite setting; Early warning systems for delinquency and Customer retention and churn prediction
• Collaborate with business stakeholders (e.g., Credit, Product, Collections, Marketing) to embed model-driven insights into strategic planning and operational execution.
• Translate complex analytical outputs into clear, actionable recommendations for non-technical audiences.
• Monitor and maintain model performance, ensuring relevance and accuracy over time.
• Maintain and improve models used to identify profitability at an individual customer level.
• Document model development and validation processes for internal governance and external regulatory review.
• Contribute to the design of data-driven strategies that enhance portfolio performance, customer experience, and risk management.

Qualifications and Experience

• Minimum qualification: Bachelor’s degree in Actuarial Science, Statistics, Mathematics, Engineering or a related quantitative discipline
• Preferred qualification: A relevant postgraduate qualification
• Experience: A minimum of 3 - 5 years' of experience in credit analytics, preferably within banking or financial services.
• Demonstrated experience in predictive modeling and translating models into business strategies.
• Familiarity with credit lifecycle processes and risk management frameworks.
• Understanding of model governance, validation, and regulatory compliance (IFRS 9, Basel Accords, NCA)
• Experience working with credit bureau data and alternative data sources.
• Proficient in SAS, SQL, Python, and R for data manipulation, modeling, and analysis.
• Experience with data visualization tools (e.g., Power BI, Tableau) is advantageous
• Strong business acumen and ability to link technical outputs to strategic objectives.
• Excellent communication and stakeholder engagement skills.
• Able to work independently and collaboratively in a fast-paced environment.

End Date: November 11, 2025