Fraud Data Scientist - (514) at BankservAfrica

Your key responsibilities include:

• Ensure individual deliverables are aligned to BU strategy, documented, clearly understood and regularly reviewed
• Provide subject matter expertise for future data driven fraud/analytics related projects for TFM
• Reviewing, analysing, and evaluating ideas, Develop and optimise core fraud detection models on BankservAfrica’s payment streams
• Manage client risk profiles by tuning detection models and thresholds to balance client risk requirements (hit rates, false positive rates, alert volumes etc)
• Ad hoc investigations of system output anomalies and general troubleshooting
• Monitor system performance according to multiple metrics at both an industry level and per client
• Manage data issues relating to detection and the incorporation of new data feeds when required/available
• Data engineering support for the acquisition of quality fraud data
• Data wrangling evaluation to minimise validation errors
• Technical to business communication
• Ad hoc investigations of system output anomalies and general troubleshooting
• Contribute to department publications on actionable insight in line with proven data science use cases.

QUALIFICATION / KNOWLEDGE

• MSc or BSc - Applied mathematics, mathematics of finance, statistics, actuarial science or equivalent
• Data analytics life cycle
• Data engineering
• Payment fraud
• Good communication (written, oral) and interpersonal skills
• Organise and manage multiple tasks
• Work autonomously and in teams

EXPERIENCE:

• 5 years’ related experience
• Big data analytics
• Scripting and programming
• Statistical modelling
• Financial industry
• Fraud detection models
• Data wrangling
• Expert in MS Office, SQL
• Advantageous: Machine learning techniques, Oracle, NetReveal, RStudio, Python