Note: The job is a remote job and is open to candidates in USA. SouthState Bank is a financial institution with deep community roots and a commitment to helping customers and employees succeed. The FIU Fraud Data Analyst uses data analysis, investigative judgment, and fraud analytics to identify and mitigate financial crime risks, improve fraud detection strategies, analyze transactions and alerts, and support risk-based reporting and escalation. The role collaborates with fraud, technology, security, compliance, and business teams to strengthen controls and reduce fraud losses.
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
Skills
- Bachelor's degree in Data Analytics, Data Science, Statistics, Finance, Accounting, Criminal Justice, Business, Computer Science, Information Systems, or a related field preferred
- 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
- 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
- Strong 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
- 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
- Equivalent related experience may be considered
- 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
Benefits
- Remote work arrangement
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