About this role
Job DescriptionHello Future Data Scientist 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 CanDevelop and implement machine learning models to detect and prevent fraud in paymentsBuild and optimise real-time fraud scoring and decisioning systemsAnalyse and query large datasets to uncover fraud patterns and insightsUse tools such as Python, SQL, Spark, and SAS to build scalable data solutionsWork within and enhance fraud capabilities across payments platformsContinuously improve fraud detection accuracy while reducing false positivesCollaborate across technology, operations, and product teams to deliver integrated solutionsContribute to the modernisation of payments ecosystems through data and AIEnsure compliance with regulatory, audit, and risk frameworksDeliver proactive, innovative solutions that improve customer outcomes and service deliveryYou Will Be an Ideal Candidate If YouHave 3–5 years’ experience in data science or AI roleHave strong experience in machine learning applied to fraud detectionExperience 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 scienceSQL for querying large transactional datasetsBig 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 systemsHave exposure to Kafka (or equivalent) plus model deployment frameworksHave exposure to core banking/payment systemsPrior experience in banking, fintech, or payments industry is highly desirableHold a degree in Data Science, Computer Science, Mathematics, Statistics, or similarYou Will Have Access ToOpportunities to work on cutting-edge AI and fraud detection use casesA collaborative environment driving payments innovation at scaleContinuous learning and development in advanced analytics and machine learningCross-functional exposure across business, technology, and operations teamsWe Can Be a Match If You AreCurious and adaptable in a fast-changing environmentPassionate about fraud prevention and payments innovationAble to analyse complex datasets and translate insights into actionA strong collaborator who thrives in high-performing teamsApply now if you are interested in taking the next step. We look forward to engaging with you! Important Closing Date NoteTake 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.
- LOCATION
- Johannesburg, Gauteng
- WORK MODE
- On-site
- JOB TYPE
- Full-time
- POSTED
- 28 Sept 2026
Source: FirstRand / FNB Careers