Senior Data Scientist

Absa Group; Johannesburg; On-site; ZAR 700,000 - 900,000; Full time

Job summary

A leading banking institution in Johannesburg is seeking a Senior Data Scientist to enhance credit processes through machine learning and automation. The ideal candidate will have a robust background in data science, particularly within credit risk, and possess strong analytical skills. Join our team to drive innovation in scoring and lending practices.

Qualifications

• Bachelor’s degree in a quantitative discipline essential.
• Minimum 5 years’ experience in applied analytics and data science.

Responsibilities

• Develop credit risk models for Business Banking segments.
• Collaborate with stakeholders to drive data-led decision-making.
• Monitor and refine model performance post-deployment.

Skills

Analytical thinking

Structured planning

Strong communication skills

Proficiency in SAS

Expertise in SQL

Experience with Python

Education

Bachelor’s degree in Actuarial Science, Mathematics, Physics, Statistics, Computer Science, Econometrics

Tools

SAS

SQL

Python

R

AWS

Azure

Job description

Empowering Africa’s tomorrow, together…one story at a time.

With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

Job Summary

The Business Banking Credit area is undergoing a critical transformation to enable faster credit origination, unlock growth segments, and support automation of manual processes. This role is integral in enabling scored lending and automation, particularly for low-ticket credit applications. The Senior Data Scientist will drive the design, development, and deployment of scalable machine learning and AI solutions that will expedite credit decisions, improve customer turnaround times, and enhance overall credit lifecycle efficiency.

Job Description

Accountability: Technical Delivery

• Develop and implement credit risk, fraud, debt collection, and portfolio management models tailored to the Business and Commercial Banking segments.
• Apply advanced statistical and data mining techniques to derive patterns and actionable insights from large volumes of tabular and structured data.
• Own the entire data science pipeline—from data ingestion and transformation to model development and operationalisation—ensuring seamless integration into business processes.
• Monitor, evaluate, and refine model performance post-deployment, ensuring accuracy, fairness, and compliance with internal risk governance and external regulatory standards.
• Leverage new data sources and assess the effectiveness of data gathering techniques to enhance model robustness and coverage.

Accountability: Stakeholder Engagement

• Collaborate closely with Credit, Risk, Product, Technology, and Business stakeholders to identify high-impact opportunities for data science applications that solve real business problems.
• Drive data-led decision-making by translating complex analytics into clear, actionable recommendations aligned to business strategy and risk appetite.
• Design, execute, and interpret A/B tests to evaluate the effectiveness of credit strategies, scorecard changes, and policy enhancements.
• Present findings through compelling visualisations, dashboards, and storytelling, effectively communicating technical outcomes to both specialist and non-technical audiences.

Accountability: People and Project Collaboration

• Work collaboratively in multidisciplinary teams to embed models and analytics into the scored lending platform and overall credit lifecycle.
• Provide subject matter expertise and thought leadership on model development and deployment within the broader Business Banking credit automation programme.
• Support the Head of Scored Lending and Automation in building a scalable scored lending capability, contributing to the establishment of a Data Science Centre of Excellence.
• Foster a culture of curiosity, continuous improvement, and innovation across the team.

Education and experience required

• Bachelor’s degree: Actuarial Science, Mathematics, Physics, Statistics, Computer Science, Econometrics, or a related quantitative discipline is essential.
• Minimum 5 years’ experience in applied analytics, predictive modelling, and data science, preferably within credit risk, fintech, or financial services.

Knowledge and skills: (Maximum of 6)

• Analytical and structured thinking and planning skills.
• Ability to build strong rapport across all levels of management within the group.
• Strong verbal and written communication and presentation skills.
• Expert proficiency in SAS and SQL; experience with Python, R, or similar tools advantageous.
• Solid understanding of supervised learning algorithms and experience applying them in credit risk or fraud contexts.
• Familiarity with cloud platforms such as AWS or Azure.
• Strong analytical and problem-solving skills with demonstrated ability to derive business value from data.
• Knowledge of credit policy development and scorecard techniques is a strong advantage.

Education

Bachelor`s Degrees and Advanced Diplomas: Physical, Mathematical, Computer and Life Sciences (Required)

Absa Bank Limited is an equal opportunity, affirmative action employer. In compliance with the Employment Equity Act 55 of 1998, preference will be given to suitable candidates from designated groups whose appointments will contribute towards achievement of equitable demographic representation of our workforce profile and add to the diversity of the Bank.

Absa Bank Limited reserves the right not to make an appointment to the post as advertised