Job Description
We are seeking a proactive and analytical Associate Fraud Analyst to join our motivated and collaborative Fraud Analytics team. In this regional role, you will be crucial in safeguarding our logistics operations by detecting and preventing fraudulent activities. You will use data analytics to identify patterns and vulnerabilities, designing and implementing process changes to tighten controls on the ground. This role is perfect for individuals passionate about data analytics, fraud prevention, and continuous process improvement. You will work closely with cross-functional teams in various markets to tailor strategies to local needs and regulatory requirements.
- Fraud Detection and Data Analytics: Utilise Python and other analytical tools to analyse large datasets to identify anomalies, trends, and patterns that could indicate fraudulent activity or process weaknesses. Implement algorithms and models to detect and predict fraud within logistics operations
- Process Improvement: Design and implement process changes to enhance control measures and reduce the risk of fraud within logistics operations. Collaborate with on-the-ground teams to ensure effective execution and compliance
- Reporting and Documentation: Develop fraud and loss indicators and reports to track trends and the effectiveness of fraud prevention measures. Maintain comprehensive documentation of findings and actions taken
- Cross-Functional Collaboration: Work closely with regional teams, including regional operational excellence team, product management, local teams operations and risks teams, to develop and refine fraud detection tools and processes that address logistics-specific challenges
- Incident Investigation: Lead investigations into fraud cases within logistics, gather relevant data, and support resolution efforts. Communicate findings and recommendations to stakeholders to prevent future occurrences
- Continuous Monitoring and Adaptation: Continuously assess and improve fraud prevention strategies and controls to ensure they remain effective and relevant. Stay updated on emerging logistics fraud trends and regulatory changes
Requirements
- Education: Bachelor's degree in a quantitative field. Candidates with 0-1 years of experience are welcomed
- Technical Skills: Proficiency in Python for data analysis and process automation. Ability to work with large data sets
- Analytical Skills: Strong analytical and problem-solving abilities, with an aptitude for detecting and investigating complex fraud schemes within logistics
- Attention to Detail: Exceptional attention to detail and accuracy in analysing data and implementing process changes
- Communication: Excellent verbal and written communication skills, capable of conveying technical information and recommendations to diverse stakeholders
- Team Player: Ability to work collaboratively in a team environment, supporting the development and execution of fraud prevention strategies across different regions
- Adaptability: Flexibility to adapt to new challenges and work effectively in a dynamic environment across multiple markets
