Senior Fraud Data Scientist

1 month ago

Johannesburg, South Africa South African Bankers Services Company Pty Ltd Full time

**Job Description**:
BankservAfrica form part of the South African National Payments System and are a trusted partner of the financial industry, including banking institutions, and therefore require that employees adhere to unwavering standards of honesty and transparency in performing their duties.

PURPOSE

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

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