Analyze portfolio exposures and build data-driven insights.
Automate credit risk reporting processes for Loss Forecasting covering all US business entities.
Extract, transform, and analyze credit risk and portfolio data.
Develop automated reporting and analytical tools using Python.
Monitor key risk indicators.
Collaborate with risk owners to improve controls and reporting workflows.
Present insights and recommendations to stakeholders.

Requirements

Bachelor’s degree in Finance, Economics, Data Science, Statistics, or a related field – Required.
3+ Years analyzing credit risk or financial portfolio data within banking or financial services environments – Required.
Advanced proficiency in Python (including Pandas and NumPy), SQL, and data visualization tools such as Power BI or Tableau to analyze, manage, and present structured credit risk data – Required.
Strong understanding of credit risk concepts, financial statements, portfolio risk metrics, and predictive modeling techniques, including risk indicator development – Required.
Experience working with large-scale financial datasets within highly regulated environments, including familiarity with model validation, risk governance, and regulatory reporting frameworks – Preferred.
Strong analytical thinking with the ability to interpret complex datasets, identify meaningful trends, and translate insights into actionable recommendations.

Benefits

We value your impact: Your contribution matters and it’s recognized. You can expect a fair and competitive rewards package that reflects the impact you create and the value you deliver. We know rewards go beyond numbers.

Applicant Tracking System Keywords

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

Hard Skills & Tools

PythonPandasNumPySQLdata visualizationPower BITableaupredictive modelingdata analysisautomated reporting

Soft Skills

analytical thinkingcommunicationcollaborationpresentation skillsproblem-solving