Technical Fraud Analyst (Western Cape) at Flash Group

Description

• The role will encompass analysing large datasets to identify patterns and anomalies, develop predictive models to anticipate fraudulent behaviour, and work closely with cross-functional teams to implement and refine fraud detection systems.

RESPONSIBILITIES:

• Analyse large datasets by conducting thorough analysis of extensive datasets to identify patterns and anomalies indicative of fraudulent activity.
• Research new techniques by staying updated on the latest fraud detection methodologies and incorporate them into the organisation’s practices.
• Evaluate system performance regularly, by assessing and improving accuracy and efficiency of fraud detection systems and models.
• Ensure data integrity and security of the data throughout the analysis process to protect sensitive information.
• Provide insights and recommendations based on data analysis to enhance overfall fraud prevention and detection measures.
• Implement real-time analytics to detect and respond to fraudulent activities as they occur, minimising potential damage.
• Regularly update and refine fraud detection models and techniques based on new data and emerging fraud trends.
• Collaborate with internal teams, to develop and implement comprehensive fraud prevention strategies.
• Develop and implement systems for identifying unusual behaviours or transactions that could indicate fraudulent activity.

Requirements

MINIMUM REQUIREMENTS:

• Bachelor’s degree in a related field such as data science, computer science, statistics, mathematics, or engineering.
• Two (2) years’ experience in fraud/data related field.
• Experience working with large datasets and databases is essential.

REQUIRED KNOWLEDGE / TECHNICAL SKILLS:

• Candidates should possess strong analytical and problem-solving skills, experience with programming languages like R, SQL, Python and Java 
• Solid understanding of statistical methods and data analysis techniques.
• Familiarity with machine learning and artificial intelligence.

COMPETENCIES / ATTRIBUTES:

• Analytical Thinking: Ability to systemically analyse complex data, identify patterns, and trends.
• Attention to Detail: Meticulous focus on data accuracy and precision in identifying discrepancies.
• Problem-Solving Skills: Proficiency in developing innovative solutions to detect and prevent fraud.
• Communication Skills: Effectiveness in conveying complex findings and insights to non-technical stakeholders.
• Adaptability: Flexibility to adjust to new challenges, tools, and techniques in the evolving fraud landscape.
• Critical Thinking: Skill in evaluating situations logically and making informed decisions based on data.
• Ethical Integrity: Commitment to ethical practices and maintaining confidentiality in handling sensitive data.
• Creativity in Developing Solutions: Inventiveness in devising new strategies and methods to combat fraud.
• Time Management Skills: Efficient in managing multiple tasks and meeting deadlines in a fast-paced environment.
• Persistence: Tenacity in exploring data and testing models until effective solutions for fraud detection are found.