
Senior Fraud Data Analyst
23 hours ago
Job Overview
The Fraud Risk Manager will contribute as a subject matter expert and support data, machine learning models, and artificial intelligence technology for investigation and loss mitigation teams. This individual will maintain the effectiveness of investigation tools and technologies, data processes, and reporting that deliver robust and timely data insights.
- Hands-on experience in analytics and data science is essential.
- Model development and exposure to fraud detection are required skills.
- Good understanding of large language models and other new techniques is necessary.
- Data deep dive, insight generation, dashboard reporting, and presentation skills are crucial.
- End-to-end project delivery and stakeholder management are key responsibilities.
Key Accountabilities
The Fraud Risk Manager will be responsible for:
- Analyzing large amounts of information to discover trends and patterns.
- Combining models through ensemble modeling.
- Presenting information using data visualization techniques.
- Proposing solutions and strategies to business challenges.
- Collaborating with engineering and product development teams.
- Creating and enforcing policies for effective data management.
- Assisting with reports and data extraction when needed.
- Formulating techniques for quality data collection to ensure adequacy, accuracy, and legitimacy of data.
System Validation
The Fraud Risk Manager will oversee the following activities:
- Monitoring fraud trends and investigating emerging threats.
- Building predictive models and machine-learning algorithms.
- Analyzing structural requirements for new software and applications.
- Optimizing new and current database systems.
- Reviewing existing control environments and assessing their effectiveness against known fraud schemes.
- Providing insight as a subject matter expert on process and control fraud leakages.
People Management
The Fraud Risk Manager will work collaboratively with a diverse team of operational agents, fraud risk managers, data analysts/scientists, business insight analysts, and subject matter experts. This individual will also support team members to locate and define new process improvement opportunities.
Educational Qualifications
- A master's degree in statistics, economics, or engineering, or professional education in data science is preferred.
- Good knowledge of Python, R, SQL, MS Excel, and SQL database & coding is required.
- At least a bachelor's degree in mathematics, computer science, engineering, economics, or statistics is necessary.
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