Fraud Data and Analytics Analyst

Regions Bank•Atlanta, GA

1d•$79,223 - $100,070

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 that supports leaders’ data-driven fraud detection decisions and helps protect the bank from financial loss. The analyst examines fraud threats and their impact, identifies opportunities to reduce net losses or improve operational efficiency, evaluates fraud-rule strategies, and develops transaction and system monitoring for suspicious activity. The position also produces reports and presentations, provides insight into trends and operational impacts, supports data automation and governance, and maintains data quality. The analyst keeps abreast of fraud trends and may guide junior analysts. This is a full-time position exempt from timekeeping requirements under the Fair Labor Standards Act and not eligible for overtime pay. The position is based at the Riverchase Operations Center in Hoover, Alabama, and must be within a reasonable driving distance of Birmingham, Alabama; Atlanta, Georgia; or Charlotte, North Carolina. Regions does not provide relocation assistance or sponsor work visas for this position. Applicants must be currently authorized to work in the United States on a full-time basis.

Requirements

Master’s degree in Business, Computer Science, Information Systems, Finance, Statistics, Criminal Justice, Mathematics, Engineering, or a related field, and two years of experience in data analytics or a related role; alternatively, a bachelor’s degree in one of these fields and four years of experience in data analytics or a related role.
Advanced analytical skills.
Demonstrated leadership capabilities.
General knowledge of the banking industry and 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.

Nice To Haves

Experience with analytical software and programming 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.
Ability to analyze large, complex datasets to identify trends, patterns, and anomalies.
Strong understanding of KPIs, metrics, and business performance indicators.
Advanced SQL skills for data extraction, transformation, and validation, including complex joins, CTEs, and performance optimization.
Experience designing interactive dashboards and reports using Power BI or Tableau, and applying data storytelling, visualization design, and user-centered reporting practices.
Experience with data pipelines, transformations, and data cleansing; understanding of source systems, data lineage, and refresh schedules.
Experience with Python, Spark, and Snowflake systems.
Ability to deploy code to production using Git and Harness Pipelines.
Knowledge of dimensional modeling, including star and snowflake schemas, and structuring fact and dimension tables for efficient reporting.

Responsibilities

Analyze fraud-based threats affecting the bank; gather and analyze data, report findings, determine how fraud was conducted, quantify losses, and recommend ways to address threats and mitigate losses.
Identify opportunities to reduce fraud losses or improve operational efficiency and effectiveness.
Assess current rule strategies and analyze potential enhancements.
Develop and execute transaction and system monitoring for unusual or suspicious merchants and other redemption activities.
Assist in preparing visual reports and presentations for management.
Modify reports to make them valuable, readable, and presentable to stakeholders.
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 to classify and store 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, data mining, and data management.
Monitor data and analytics trends and seek opportunities for continuous improvement.
Partner with the centralized Data Governance team to implement and support data governance and data quality requirements.
Stay current on best practices and fraud trends to optimize and refine controls used to detect fraudulent activity.
May guide junior analysts and ensure they receive appropriate training and tools.