Credit Risk Data Analyst

City National Bank of Florida•Coral Gables, FL

21h

About The Position

The Credit Risk Data Analyst performs analytical work supporting the bank’s credit risk management activities. The role evaluates credit risk data, develops portfolio insights, and supports decision-making using established analytical methods and reporting frameworks. The analyst collaborates with internal partners to ensure data accuracy, strengthen risk reporting, and maintain alignment with internal standards and regulatory expectations, applying judgment and analytical expertise within defined policies. The position analyzes loan portfolios and credit risk indicators, conducts stress testing and scenario evaluations, develops and maintains dashboards and reporting tools, and communicates findings to senior management and risk committees. It also supports data governance, data-quality controls, regulatory exams, audits, internal reviews, Enterprise Risk Management efforts, and cross-functional risk initiatives. The analyst uses approved AI and automation tools responsibly, with appropriate human oversight and attention to regulatory compliance, data privacy, and risk management standards.

Requirements

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 and demonstrated experience using 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 and apply judgment to data validation, reconciliation, and interpretation within established policies and frameworks.
Strong written and verbal communication skills, including the ability to clearly and structurally convey analytical findings to non-technical audiences.
High attention to detail and critical-thinking ability when reviewing data, analytical results, or risk indicators.
Use approved AI and automation tools while maintaining appropriate human oversight, regulatory compliance, data privacy, and risk-management standards.
Adaptability to emerging technologies and commitment to continuous process improvement through responsible AI adoption.
Bachelor’s degree in Finance, Economics, Statistics, Mathematics, Data Analytics, or a related field, or an equivalent combination of education and/or relevant professional experience.

Nice To Haves

Progress toward or completion of a professional certification such as FRM, CFA, or PRM.

Responsibilities

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 to assess portfolio outcomes under varying economic conditions.
Contribute to the development and monitoring of 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 through established processes.
Maintain documentation about 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 related 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.
Use approved AI and automation tools to improve productivity, quality, and decision-making while maintaining human oversight and complying with regulatory, privacy, and risk-management standards.
Adapt to emerging technologies and contribute to process improvement through responsible AI adoption.