Welcome to FNB, where we design for shapeshifters and deliver products and services that make us incredibly proud of the people who make it happen.
As part of our team in FNB Commercial EFT, you will be surrounded by unique talents, diverse minds, and an adaptable environment that lives up to the promise of staying curious. Now’s the time to imagine your potential in a team where experts come together to modernise payments and drive intelligent fraud detection using AI and machine learning.
Are You Someone Who Can
- Develop and implement machine learning models to detect and prevent fraud in payments
- Build and optimise real-time fraud scoring and decisioning systems
- Analyse and query large datasets to uncover fraud patterns and insights
- Use tools such as Python, SQL, Spark, and SAS to build scalable data solutions
- Work within and enhance fraud capabilities across payments platforms
- Continuously improve fraud detection accuracy while reducing false positives
- Collaborate across technology, operations, and product teams to deliver integrated solutions
- Contribute to the modernisation of payments ecosystems through data and AI
- Ensure compliance with regulatory, audit, and risk frameworks
- Deliver proactive, innovative solutions that improve customer outcomes and service delivery
You Will Be an Ideal Candidate If You
- Have 3–5 years’ experience in data science or AI role
- Have strong experience in machine learning applied to fraud detection
- Experience with machine learning frameworks (e.g., scikit‑learn, TensorFlow, PyTorch)
- Knowledge of fraud detection techniques (e.g., supervised/unsupervised learning, anomaly detection, graph analytics)
- Are proficient in:
- Python for data science
- SQL for querying large transactional datasets
- Big data tools (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Analytics platforms (SAS Studio, SAS Enterprise Guide/Miner)
- Have experience working with real-time scoring or decisioning systems
- Have exposure to Kafka (or equivalent) plus model deployment frameworks
- Have exposure to core banking/payment systems
- Prior experience in banking, fintech, or payments industry is highly desirable
- Hold a degree in Data Science, Computer Science, Mathematics, Statistics, or similar
You Will Have Access To
- Opportunities to work on cutting-edge AI and fraud detection use cases
- A collaborative environment driving payments innovation at scale
- Continuous learning and development in advanced analytics and machine learning
- Cross-functional exposure across business, technology, and operations teams
We Can Be a Match If You Are
- Curious and adaptable in a fast-changing environment
- Passionate about fraud prevention and payments innovation
- Able to analyse complex datasets and translate insights into action
- A strong collaborator who thrives in high-performing teams
Apply now if you are interested in taking the next step. We look forward to engaging with you!
Important Closing Date Note
Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.
05/10/26All appointments will be made in line with FirstRand Group’s Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.
Skills Required
- 3-5 years of experience in data science or an AI role
- Strong experience applying machine learning to fraud detection
- Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch
- Knowledge of supervised and unsupervised learning, anomaly detection, and graph analytics
- Proficiency in Python for data science
- Proficiency in SQL for querying large transactional datasets
- Experience with big data tools such as Spark and Hadoop
- Experience with cloud platforms such as AWS, Azure, or GCP
- Experience with analytics platforms such as SAS Studio and SAS Enterprise Guide/Miner
- Experience with real-time scoring or decisioning systems
- Exposure to Kafka or an equivalent streaming technology
- Exposure to model deployment frameworks
- Exposure to core banking or payment systems
- Degree in Data Science, Computer Science, Mathematics, Statistics, or a similar field
- Prior banking, fintech, or payments industry experience
What We Do
FirstRand is a portfolio of integrated financial services businesses offering transactional, lending, investment and insurance products and services. The group seeks to build long-term franchise value and deliver superior, sustainable returns within acceptable levels of volatility. Its corporate centre houses key functions—including risk, compliance, governance, internal audit, treasury, finance and tax—that support the broader group and its operating businesses.
