Fraud Analyst

Data Analytics

  • AvailabilityPermanent
  • Experience5+ Years
  • Share

Fraud Analyst

Data AnalyticsGauteng

A leader in the payments industry, based in Johannesburg, is looking for a Fraud Analyst who is responsible for development, optimization, maintenance and evolution of fraud data models. The primary goal of the role is to make optimal use of existing and new data sources to develop high performance detection/risk models to address bank client risk requirements. Key abilities include the ability to leverage off of multiple skillsets, including data handler, technical analyst, communicator, and trusted advisor.

Key stakeholders the Fraud Data Analyst will engage with are:
- Fraud Team (Business Owner, Fraud Data Scientists, Stakeholder Relationships)
- Internal departments (IT Ops: Infrastructure, Networks, Applications, Database, Service Desk)
- Service providers, industry bodies & vendors

Responsibilities:


Financial Management
- Demonstrate cost awareness and control and report on revenue, costs and volumes where applicable
Stakeholder Management
- Build, influence, and manage key stakeholder relationships (internal and external) and expectations within all direct areas of responsibility.
- Understand customer needs and supplier contribution and utilize to drive optimal operational results
- Ensure delivery on internal and external stakeholder requirements/SLA’s
Strategic Alignment
- 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
- Develop and optimise core fraud data models on payment streams
- 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
- Policies and procedures: Develop, amend and implement relevant policies and procedures
- Compliance: Ensure compliance with relevant policies & procedures, regulation and legislation
- Risk: Ensure risks are reported on and mitigated
- People Processes: Commitment to a fair and transparent performance management plan.
- People Development: Balanced participation in individual and team engagement sessions. Commitment and achievement in agreed career development plan

Qualifications:
- Appropriate degree related to data analysis (scientific or commercial)
- Advanced SQL, data analysis and modelling sills required
- Data analytics life cycle
- Good communication (written, oral) and interpersonal skills
- Organise and manage multiple tasks
- Work autonomously and in teams

Experience:
- 3-5 years’ related experience
- Big data analytics
- Scripting and programming
- Financial industry
- Fraud detection models
- Data wrangling
- Expert in MS Office, SQL
- Advantageous: Machine learning techniques, Oracle, NetReveal, RStudio, Python

Skills
  • fraud
  • big data
  • SQL
  • Risk Models
  • Detection Models
Requirements
  • Education Tertiary Degree
  • Experience 5+ Years

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