FIU Fraud Data Analyst

SouthState Bank•Orlando, FL

1d•Hybrid

About The Position

The FIU Fraud Data Analyst is responsible for using data, investigative judgment, and fraud analytics to identify, investigate, and mitigate internal and external financial crime risks against the Bank. This role analyzes large and complex datasets, fraud alerts, customer and transaction activity, and emerging fraud trends to support timely risk-based decisions, reduce fraud losses, strengthen controls, and ensure regulatory expectations are met. The position partners with FIU leadership, Fraud Operations, Digital Banking, Treasury Management, Information Technology, Information Security, Compliance, and other business partners to develop actionable insights, improve fraud detection strategies, and support effective reporting and escalation. It is the policy of SouthState Bank to comply with the Bank Secrecy Act (BSA), USA PATRIOT Act, and the requirements of the Office of Foreign Assets Control (OFAC), and other related anti-money laundering/ anti-terrorist financing initiatives. The Bank has established a Bank Secrecy Act/ Anti-Money Laundering/Office of Foreign Assets Control (BSA/AML/OFAC) Compliance Program, covering all requirements of the BSA, USA PATRIOT Act and OFAC rules and regulations. Upon completion of required training, the Board of Directors of SouthState Bank shall hold each employee accountable for adhering to the established operating procedures and internal controls as set forth in the Bank’s BSA/AML/OFAC Program. Continued instances of non-compliance or willful violation of law may result in disciplinary action, up to and including termination.

Requirements

Bachelor’s degree in Data Analytics, Data Science, Statistics, Finance, Accounting, Criminal Justice, Business, Computer Science, Information Systems, or a related field preferred.
Equivalent related experience may be considered.
Minimum of 5 years of fraud, financial crimes, BSA/AML, banking operations, risk management, data analytics, or related experience in a financial institution or similar regulated environment;
Experience conducting fraud investigations, analyzing transactional activity, and identifying patterns indicative of fraud or financial crime;
Minimum of 2 years’ experience querying, analyzing, and reconciling large datasets using SQL-based databases, Snowflake, Excel, or similar tools;
Experience creating management reports, dashboards, trend analyses, or data-supported recommendations;
Working knowledge of SQL, Snowflake, relational databases, data extraction, data validation, and data quality concepts;
Working knowledge of Microsoft Excel, including pivot tables, formulas, data cleaning, and analytical functions;
In-depth knowledge of fraud typologies and associated bank fraud schemes, including online account opening, account takeover, social engineering, mule activity, mobile, digital, check, ACH, wire, debit card, and payment fraud;
Familiarity with payment types and digital banking products, including Zelle, Bill Payments, Bank-to-Bank payments, ACH, wires, checks, debit cards, and related customer authentication controls;
In-depth knowledge of BSA/AML regulations related to suspicious activity monitoring, escalation, and reporting;
Strong understanding of bank operations, including navigating banking systems, interpreting teller and customer transactions, and evaluating account relationships;
Advanced analytical, critical thinking, and problem-solving skills with the ability to interpret complex data and identify meaningful patterns, anomalies, and trends;
Strong investigative judgment and ability to identify fraudulent, unusual, or suspicious activity and determine when escalation is required;
Ability to query, analyze, reconcile, and summarize large datasets accurately and efficiently;
Ability to translate data findings into clear business recommendations, risk-based actions, and concise executive-level reporting;
Strong understanding of fraud typologies, payment risk, customer behavior, account activity, digital banking risk, and internal control concepts;
Sound judgment, discretion, and integrity when handling confidential customer, employee, investigative, and bank information;
Ability to work independently, prioritize competing deadlines, and make timely decisions in a fast-paced, high-risk environment;
Strong attention to detail, data quality, documentation, and audit trail requirements;
Proficiency with Microsoft Outlook, Word, Excel, PowerPoint, and data visualization or reporting tools such as Power BI, Tableau, or similar platforms;
Excellent oral and written communication skills, including the ability to explain technical or analytical findings to non-technical stakeholders;
Ability to collaborate effectively with business lines, operations, technology, risk, legal, compliance, and management partners;
Ability to read, analyze, and interpret applicable Federal and State banking regulations, internal policies, and procedures related to fraud, BSA/AML, OFAC, privacy, and information security.
Must be able to remain seated or work standing in a confined area on a computer for a minimum of four (4) hours each workday.
Must be able to constantly use hands and fingers to enter data through or on a computer or answer a phone throughout most of an eight (8) hour shift.
Must be able to hear and communicate with coworkers and customers throughout the day.
Must be able to function in a professional, business office environment and act and dress appropriately for same, consistent with the Bank’s grooming and dress codes.
Must demonstrate excellent people skills with customers and coworkers.
Must be willing to function as a team member.
Must be willing to demonstrate commitment to South State Bank’s mission and goals.

Nice To Haves

Experience with fraud detection systems, case management systems, digital banking platforms, core banking systems, payment channels, or transaction monitoring tools preferred;
Minimum of 2 years experience supporting fraud strategy, rule tuning, control enhancement, alert optimization, or loss mitigation initiatives preferred.
Knowledge of data visualization, dashboarding, or reporting tools such as Power BI, Tableau, or similar platforms preferred;
Familiarity with Python, R, SAS, model monitoring, statistical analysis, or machine learning concepts used in fraud detection preferred but not required;
CAMS (Certified Anti-Money Laundering Specialist), CAFP (Certified AML and Fraud Professional), CFE (Certified Fraud Examiner), or data analytics-related certification preferred.

Responsibilities

Evaluate fraud detection rules, monitoring logic, alert performance, false positives, and data quality issues; recommend enhancements to improve detection effectiveness and operational efficiency
Develop, maintain, and enhance dashboards, recurring reports, trend analyses, and ad hoc data views to identify fraud patterns, emerging typologies, control gaps, and loss exposure
Identify emerging fraud trends, attack patterns, mule activity, account takeover indicators, synthetic identity concerns, suspicious online account opening activity, social engineering indicators, and other financial crime risks
Query, extract, validate, and analyze large datasets using SQL-based databases, Snowflake, Excel, and other approved analytical tools to support fraud investigations and strategy development
Analyze fraud alerts, account activity, customer behavior, transaction patterns, and other data sources to identify unusual, suspicious, or potentially fraudulent activity
Research and analyze high-risk transactions across payment channels, including digital banking, Zelle, Bill Pay, Bank-to-Bank transfers, debit card, wires, ACH, checks, and other products as applicable
Communicate internal control deficiencies, data limitations, system issues, and fraud vulnerabilities identified during analytical or investigative work
Provide analytical support, peer guidance, training, and subject matter expertise to team members as needed
Take ownership of all tasks and challenges that they encounter in the operation of their assigned position.