Fraud Data Scientist

In this role, you'll analyse data to spot fraud patterns and create models to prevent fraudulent activities. Using machine learning and statistical techniques, you'll develop algorithms to protect financial systems. You'll work with teams to implement solutions that improve fraud prevention and support risk management. Key Responsibilities: Align deliverables to business strategy with regular reviews. Provide expertise on fraud and analytics-related projects. Develop and optimize fraud detection models for payment streams. Manage client risk profiles and adjust detection models accordingly. Troubleshoot system anomalies and support data acquisition. Monitor system performance and contribute to data wrangling and validation. Communicate technical information to business and technical teams. Contribute to publications on actionable insights and data science use cases. Qualifications/Knowledge: Must have AWS experience. MSc or BSc in Applied Mathematics, Statistics, Actuarial Science, or related fields. Expertise in data analytics, data engineering, and fraud detection systems. Strong communication and organizational skills. Ability to work independently and collaborate in team settings. Experience: Minimum 5 years' experience in data science or related field. Expertise in big data analytics, statistical modelling, and programming (Python, R). Experience with fraud detection models, data wrangling, and SQL. Familiarity with machine learning techniques and platforms (e.g., Oracle, NetReveal) is a plus. Experience in the financial industry is advantageous. How to Apply:

Location: Johannesburg, ZA

Posted Date: 1/8/2025