The FedNow product team is seeking a highly skilled Fraud Data Analyst to enhance our fraud prevention strategies through advanced analytics, fraud detection tools, and data-driven insights. The ideal candidate will have strong experience in fraud analytics, statistical analysis techniques, and fraud detection models, along with a passion for mitigating fraud across the financial sector.
Key Responsibilities:
Analyze transactional and behavioral data to detect, monitor, and prevent fraud
Recommend, test, and implement new fraud rules to strengthen our organization’s fraud detection frameworks
Work with fraud analytics and modeling tools to develop, validate, promote, and monitor fraud models.
Use fraud detection tools to enable end-to-end workflows, including data ingestion, transformation, modeling, and performance monitoring.
Apply data generation and transformation techniques to ensure the integrity and quality of datasets used for fraud detection.
Perform statistical analysis and build predictive models to uncover hidden patterns and fraud risk indicators
Monitor fraud model performance and identify opportunities for optimization.
Create dashboards, reports, and materials to communicate fraud metrics and insights to internal stakeholders
Stay current on emerging fraud trends, technologies, and regulatory requirements to inform strategy.
Collaborate with specialists including data scientists, systems architects, information security architects, and product managers to develop and implement fraud prevention strategies
Qualifications:
Bachelor’s degree in data science, statistics, computer science, business, or a related field (Master’s degree preferred)
5+ years of experience in data analysis with at least 3 years in fraud analytics or prevention in the financial services industry
Hands on experience with fraud detection tools, including both industry-standard solutions and specialized niche tools.
Proficiency in querying and analyzing large datasets using SQL, Python, R, or similar tools
Expertise in data cleaning, transformation, and integration. Expertise in statistical and predictive analysis
Experienced in creating and validating fraud prevention rules to identify, prevent, and mitigate fraudulent activities.
Ability to communicate technical concepts effectively to technical and non-technical audiences
Strong problem-solving skills, attention to detail, and a data-driven mindset
The Federal Reserve System is committed to a diverse and inclusive workplace and to provide equal employment opportunities to all persons without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, age, genetic information, disability, or military service.
All employees assigned to this position will be subject to FBI fingerprint/ criminal background and Patriot Act/ Office of Foreign Assets Control (OFAC) watch list checks at least once every five years.
The above statements are intended to describe the general nature and level of work required of this position. They are not intended to be an exhaustive list of all duties, responsibilities or skills associated with this position or the personnel so classified. While this job description is intended to be an accurate reflection of this position, management reserves the right to revise this or any job description at its discretion at any time.
The Federal Reserve Banks believe that diversity and inclusion among our employees is critical to our success as an organization, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.
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