Credit Risk Data Analyst

City National Bank of Florida

. Evaluate loan portfolios to identify credit risk trends, concentrations, and emerging risk themes across products, industries, and geographies .

Posted 11/5/2026full-timeCoral Gables • Florida • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in credit risk analysis and data analytics, with proficiency in SQL, Python, and data visualization tools like Qlik and Power BI. Capable of interpreting complex risk data and communicating insights effectively to stakeholders while ensuring compliance with regulatory standards.

Highest-signal resume keywords

Credit Risk AnalysisSQL ProficiencyData VisualizationRegulatory ReportingAnalytical Communication

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Credit Risk ConceptsLoan Portfolio Data AnalysisStress TestingData ValidationStatistical AnalysisRisk RatingsData InterpretationAnalytical DashboardsAutomation ToolsData Quality Standards

Soft Skills

Attention to DetailCritical ThinkingWritten CommunicationVerbal CommunicationCollaboration

Tools & Technologies

SQLPythonQlikPower BITableauExcelSAS

Certifications & Qualifications

FRMCFAPRM

Industry Keywords

Banking RegulationsRisk Management FrameworksData GovernanceEnterprise Risk ManagementFinancial Services

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Evaluate loan portfolios to identify credit risk trends, concentrations, and emerging risk themes across products, industries, and geographies
Support credit risk assessments by applying judgment to underwriting practices, portfolio performance indicators, and risk rating consistency
Conduct stress-testing and scenario-based evaluations under varying economic conditions
Develop and monitor key credit risk metrics and early-warning indicators
Develop and maintain analytical dashboards and reporting tools using SQL, Python, Qlik, or similar platforms
Validate the accuracy, completeness, and consistency of data used in credit risk reporting
Interpret analytical findings and communicate insights to senior management and risk committees
Respond to analytical inquiries involving credit exposure, portfolio behavior, and performance dynamics within established guidelines
Support data-governance activities by reinforcing data-quality standards and appropriate controls
Identify data-quality gaps and partner with data engineering and technology teams to resolve issues
Maintain documentation related to data sources, analytical assumptions, methodologies, and reporting frameworks
Prepare analytical materials and supporting documentation for regulatory exams, audits, and internal reviews
Ensure credit risk analytics and reporting adhere to internal governance standards and regulatory expectations
Support Enterprise Risk Management efforts relating to model outputs, portfolio analytics, and enterprise-level reporting
Collaborate with Credit Risk, Finance, ERM, Compliance, and Technology teams on cross-functional risk initiatives
Participate in continuous-improvement efforts to enhance credit risk analytics and reporting processes
Leverage approved AI and automation tools to improve productivity, quality, and decision-making while maintaining appropriate oversight and compliance

Requirements

What you’ll need

5-7 years of experience in credit risk analysis, data analytics, or a related role within banking or financial services
2-4 years of experience working with loan portfolio data and credit risk concepts, including PD, LGD, EAD, risk ratings, and stress testing
Experience contributing to regulatory reporting or risk-management frameworks in a financial-services environment
Familiarity with banking regulations, credit-risk concepts, and governance standards supporting risk oversight
Strong analytical capability with demonstrated experience applying SQL and Excel to evaluate and interpret complex risk data
Proficiency with data visualization and business intelligence tools such as Qlik, Power BI, or Tableau
Working knowledge of statistical or programming languages such as Python, R, or SAS
Ability to work with large datasets, applying judgment to data validation, reconciliation, and interpretation within established policies and frameworks
Strong written and verbal communication skills with the ability to convey analytical findings to non-technical audiences in a clear, structured manner
High level of attention to detail and ability to apply critical thinking when reviewing data, analytical results, or risk indicators
Bachelor's Degree in Finance, Economics, Statistics, Mathematics, Data Analytics, or a related field
An equivalent combination of education and/or relevant professional experience may be considered in lieu of a degree
Progress toward or completion of professional certifications such as FRM, CFA, or PRM is considered beneficial
Responsible use of approved AI and automation tools while maintaining human oversight, regulatory compliance, data privacy, and risk management standards
Adaptability to emerging technologies and continuous process improvement through responsible AI adoption

Benefits

Comp & perks

Hybrid workplace policy
Equal opportunity employment
Reasonable accommodations during the application and hiring process