Technical Fraud Analyst

Flash; Oudtshoorn; On-site; ZAR 300 000 - 400 000; Full time

Job summary

A leading technology firm in Oudtshoorn is seeking an experienced fraud analyst to analyze large datasets and develop predictive models to combat fraudulent activity. The role requires a bachelor’s degree and two years of relevant experience. Key responsibilities include improving fraud detection systems and collaborating with cross-functional teams to implement best practices. Ideal candidates will have programming skills in R, SQL, Python, and Java, and strong problem-solving abilities.

Qualifications

• Two years of experience in a fraud/data related field.
• Experience working with large datasets and databases.

Responsibilities

• Analyze large datasets to identify patterns and anomalies indicative of fraudulent activity.
• Research new techniques in fraud detection.
• Evaluate system performance and improve fraud detection accuracy.
• Ensure data integrity and security.
• Provide insights to enhance fraud prevention measures.

Skills

Analytical skills

Problem-solving abilities

Communication skills

Attention to detail

Machine learning knowledge

Programming (R, SQL, Python, Java)

Education

Bachelor’s degree in data science, computer science, statistics, mathematics, or engineering

Job description

Overview

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.

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.