Senior Data Analyst (Fraud) at Kuda Technologies Ltd – Hybrid
Job Description
Kuda is a money app for Africans on a mission to make financial services accessible, affordable, and rewarding for every African. We’re a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love. Hence, it’s only right that we ended up with the name ‘Kuda’ which means ‘love’ in Shona, a language spoken in the southern part of Africa.
About the role
We are seeking a highly skilled and detail-oriented Fraud Analyst to join our dynamic Fraud Team. In this role, you will play a key part in managing fraud queries, proactively preventing fraud incidents, and ensuring the security of our customers’ finances.
Key responsibilities:
- Identifying and investigating cases of fraud across our various channels.
- Analyze data and information to provide insights and recommendations.
- Implementing measures to mitigate fraud risks and prevent fraudulent activities.
- Conducting Fraud risk assessment on products and services.
- Fraud data analytics to identify current trends, patterns, and threats.
- Monitoring all electronic transactions to detect suspicious patterns.
- Handling escalations and providing timely resolutions to fraud-related issues.
- Collaborating with internal stakeholders to identify trends and implement control measures.
- Providing investigative findings on reported fraud cases to customers.
- Perform other duties as required.
- Compiling and presenting detailed reports on identified fraud cases, including the methods used, the impact, and the recommended preventive measures.
Requirements
- Minimum of 4 years of experience in fraud analysis or a similar role.
- Strong analytical and problem-solving skills.
- Excellent attention to detail and ability to work with large volumes of data.
- Intermediate to advanced SQL (an advantage).
- Strong analytical and problem-solving skills.
- Experience working in a fintech or other fast-paced environment.
- Proficient in Monitoring systems and rules tuning.
- Knowledge of fraud prevention techniques and technologies.
- Proficiency in using fraud detection tools and software
- Good communication skills and ability to collaborate effectively with cross-functional teams.
- Ability to work in a fast-paced environment and handle multiple priorities.
- Proficiency in SQL for querying databases and extracting data for analysis.
- Advanced skills in data analysis and the ability to use these skills to identify patterns and anomalies that may indicate fraud.
- Bachelor’s degree in a relevant field.
