Fraud Data and Analytics Analyst - Card Fraud

Regions Bank•Texarkana, TX

1d•$59,466 - $78,300•Remote

About The Position

At Regions, the Fraud Data and Analytics Analyst transforms data into meaningful formats for operational and decision-making purposes, specializing in the analysis of fraud-based threats. The role focuses on day-to-day deliverables and works with senior analysts and managers to gather and interpret data, support data-driven decisions, strengthen fraud detection, and provide insights that help protect the bank from financial loss. The position analyzes fraud threats and their impact, identifies fraud savings opportunities, assesses rule strategies, and monitors suspicious transactions and activities. It also supports reporting and presentations for stakeholders and management; data automation, database maintenance, data quality, and governance; and ongoing model monitoring and improvement. The analyst stays current on fraud trends and best practices to refine fraud controls. The position is currently offsite, with associates primarily working from home and potentially attending onsite meetings or events as needed. The arrangement may change based on business needs; regular onsite work, including three or more full days per week, may be required. The manager determines and communicates the schedule and in-office expectations. The role may be filled at a higher level depending on the candidate’s qualifications and experience. It is exempt from FLSA timekeeping requirements and is not eligible for overtime. Regions will not sponsor work visas; applicants must be authorized to work in the United States full-time.

Requirements

Master’s degree in Business, Computer Science, Information Systems, Finance, Statistics, Criminal Justice, Mathematics, Engineering, or a related field; alternatively, a bachelor’s degree in one of these fields or a related field and two years of experience in a data analytics or related role.
Experience working on an analytics team in a data-driven environment.
Experience analyzing data associated with card authorizations.
Experience in a data analysis role on a Fraud or Fraud Analytics team.
Analytical skills.
Basic knowledge of the banking industry.
Demonstrated leadership capabilities.
General knowledge of fraud processes.
Proficiency in Microsoft Office, including Excel, Word, PowerPoint, and Outlook.
Strong verbal and written communication and organizational skills.
Strong work ethic and self-motivation.
Must be currently authorized to work in the United States on a full-time basis; Regions does not sponsor work visas.

Nice To Haves

Experience using analytical software and programming languages such as SQL, SAS, Python, Ruby, R, MATLAB, Scala, or Java.
Working knowledge of business intelligence software such as Tableau or Power BI.
Experience with big data technologies such as Snowflake, Hadoop, Hive, Impala, Spark, or Kafka.
Experience in machine learning, deep learning, or artificial intelligence.
Experience using LLMs to streamline processes.

Responsibilities

Analyze and interpret fraud-based threats affecting the bank by gathering and analyzing data, reporting findings, determining how fraud was conducted, quantifying losses, and recommending actions to management.
Identify fraud savings opportunities through net loss reduction or improved operational efficiency and effectiveness.
Assess current rule strategies and analyze opportunities for enhancements.
Develop and execute transaction and system monitoring to identify unusual or suspicious merchants and other redemption activities.
Assist in preparing readable, valuable, and presentable reports for stakeholders.
Assist in preparing visual reports and presentations for management.
Interpret and analyze data and provide insights to teams and managers about operational impact, trends, and opportunities.
Perform data analysis to support data automation.
Create and maintain databases for classifying and storing information.
Complete day-to-day deliverables and ad hoc data reports to support business needs and projects and answer data-related questions.
Ensure compliance through quality data audits, mining, and management.
Monitor data and analytics trends and pursue continuous improvement opportunities.
Partner with the centralized Data Governance team to implement and support data governance and data quality requirements.
Partner with the Model Governance team to support model governance activities, including ongoing monitoring.
Stay current on best practices and fraud trends to optimize and refine controls used to detect fraudulent activity.