Senior FDIC Data Compliance & Remediation Analyst

TD; Mount Laurel Township (NJ); Sur place; USD 72 000 - 118 000; Plein temps

Résumé du poste

TD is seeking a skilled data remediation analyst to ensure FDIC Part 370 compliance by conducting in-depth data remediation analysis, researching and quality assurance on account and customer data, and identifying exception populations. The role emphasizes accurate data, robust reporting, and timely certification readiness.

Excel proficiency, experience with large datasets, and cross-functional collaboration in a banking environment are essential.

Qualifications

• Undergraduate degree or technical certificate required.
• 5+ years of relevant experience in business/admin/ statistics/finance or related fields.
• Analytical skills and ability to interpret data and draw conclusions.
• Experience with data sources, tools, and reporting.
• Strong communication and collaboration abilities.
• Ability to mentor others and coach teammates.

Responsabilités

• Perform data remediation analysis for FDIC Part 370 compliance on deposit/account data.
• Create and maintain recurring data quality reports and dashboards.
• Identify exceptions and ensure accuracy, traceability, and completeness of records.
• Collaborate with cross-functional teams to meet regulatory and reporting requirements.
• Support data modeling, data wrangling, ETL processes, and data governance initiatives.

Connaissances

Analytical thinking

Problem solving

Data analysis

Reporting

Communication

Collaboration

Mentoring

MS Office

Discretion

Time management

Formation

Undergraduate degree or Technical Certificate

Outils

Excel

SQL (nice to have)

Description du poste

TD is seeking a skilled data remediation analyst to ensure FDIC Part 370 compliance by conducting in-depth data remediation analysis, researching and quality assurance on account and customer data, and identifying exception populations. The role emphasizes accurate data, robust reporting, and timely certification readiness.

Excel proficiency, experience with large datasets, and cross-functional collaboration in a banking environment are essential.