Fraud Data Analyst

SUMMARY

First Bank seeks a data analytics professional focused on fraud prevention and risk technology. This role develops and optimizes enterprise fraud detection strategies, analyzing complex datasets and system logs to identify and mitigate threats.

ESSENTIAL FUNCTIONS

• Autonomously analyze complex datasets to identify fraud trends, isolate root cause, and formulate recommendations to influence detection strategy and risk controls.
• Design, develop, and optimize fraud detection rules, making independent decisions on rule logic, thresholds, and control effectiveness impacting enterprise risk exposure.
• Oversee fraud detection performance and exercise independent judgment to escalate, prioritize, and recommend systemic control changes based on emerging risk patterns.
• Evaluate and strategically enhance rule performance, detection models, and develop key performance and risk data metrics.
• Establish and evolve data governance standards, procedures, and reporting frameworks that influence enterprise fraud strategy.
• Analyze complex system and transaction log data to design advanced detection strategies and lead investigative initiatives impacting fraud loss mitigation.
• Lead cross-functional initiatives and influence business decisions related to fraud data analytics across multiple lines of business.
• Develop and deliver training to drive adoption of fraud detection strategies and influence operational decision-making across teams.
• Serve as fraud data analytics subject matter expert and advisor on related strategy, detection frameworks, and control optimization.

GENERAL QUALIFICATIONS

• Knowledge & Experience: 2-3 years of financial services experience, with a focus on data analytics supporting fraud, risk, cybersecurity, or a related discipline. Bachelor’s degree in Data Science, Data Analytics, Computer Science, Business Analytics, Information Systems (MIS / CIS), Statistics / Applied Statistics, or equivalent degree in a related discipline; or equivalent years of professional experience.
• Skills: Strong foundational understanding of fraud risks or digital banking. Proven analytical and problem solving abilities. Adaptive to evolving fraud tactics and aptitude for working collaboratively. Interest in technology driven fraud prevention strategies and disciplined use of artificial intelligence (AI). Experience with data analytics and visualization tools (e.g., Tableau, Power BI, Splunk). Familiarity with enterprise data warehouse solutions (e.g., Snowflake) and basic queries.