Senior Fraud Data Scientist at BankservAfrica

PURPOSE

As a Senior Fraud Data Scientist, you play a key role in supporting the delivery of the Transactional Fraud Mitigation service by leveraging data to discover new insights and develop solutions that allow for improved decision making. This role requires strong quantitative, technical, and analytical skills to balance two competing demands - enabling a frictionless customer experience while minimising fraud risk and money laundering on real time electronic payment platforms. You will be required to use statistical and machine learning techniques to maximise the performance of systems and design algorithms and heuristics to identify high risk transactions, automating real time transaction decisions. You are expected to apply and leverage off toolkits, multiple skillsets, data engineering, advanced computing, scientific methods, statistical computation, visualization, business communication, domain expertise and associated T4 ROLE PROFILE data to contribute directly to the proactive detection of fraud and the reduction of fraud losses while developing, optimizing, maintaining and evolving fraud detection and performance models at a national level that is imperative to improving scoring performance and account for shifting fraud patterns.

You will engage with the following stakeholders:

• Fraud Team (Business Owner, Analytics and Detection Team, Stakeholder Relationships) 
• Internal departments (IT Ops: Infrastructure, Networks, Applications, Database, Service Desk) 
• Service providers, industry bodies & vendors

Your key responsibilities include:

• Work with cross departmental teams to define metrics, guidelines, and strategies for effective use of algorithms and data
• Create data mining and analytics architectures, coding standards, statistical reporting, and data analysis methodologies 
• Coordinate data resource requirements between analytics and technical teams
• Work with product managers, engineers, and analytics team members to translate prototypes into production 
• Identify fraud patterns through the monitoring of transactions Complete preliminary investigations or reviews to determine if fraudulent activity is occurring and take necessary action to close accounts as required 
• Conduct research and make recommendations on big data infrastructure, database technologies, analytics tools, services, protocols, and standards
• Drive the collection of new data and the refinement of existing data sources 
• Develop algorithms and predictive models to reduce frequency of fraudulent transactions
• Develop tools and fraudulent transaction libraries that will help analytics team members more efficiently flag fraudulent transactions

QUALIFICATIONS / KNOWLEDGE

• Degree (Honours, Masters or PHD) in Statistics, Computer Science, Engineering, Mathematics or a combination of these
• Machine learning techniques, Oracle, RStudio, Python, Hadoop, cloud infrastructure Data analytics life cycle
• Data engineering 
• Scripting and programming
• Prescriptive and Statistical modelling 
• Fraud detection models 
• Data wrangling 
• Expert in MS Office, SQL

EXPERIENCE

• 5 years’ data science experience
• Experience with malware analysis, risk analysis, and risk management
• Big data analytics
• Experience in financial industry focusing on payment fraud
• Good written and oral communication skills
• Good interpersonal skills (require a patient and empathetic attitude) 
• Have strong time management and organisational skills (must be able to organise and manage multiple tasks at a time) 
• Be able to work autonomously and in teams 
• Be comfortable working in fast-paced environments 
• Good troubleshooting skills PERFORMANCE STAN