Credit Risk Analyst Senior

Provide analysis of credit related risk for strategy development and predictive modeling, as well as lead the strategic direction of modeling and data analytics with emphasis on credit scoring, credit risk, behavioral models, loan loss and general purpose risk/profitability models.

Specific duties include: Develop, monitor, validate and maintain statistical models, perform data analysis and provide recommendations to support the execution of portfolio risk management strategies. Forecast trends, monitor statistical and machine learning models and provide data used to manage risk. Assist with data mart lake and data storage advice to ensure maintenance of robust databases. Provide expert analysis of information and models through leading data analysis tools and methodologies. Ensure consistency of model calculations development methodology, deployment and optimization, and model output in the business unit. Enhance models based on enterprise and business unit needs. Adhere to best practices and continually strive to increase knowledge and proliferation of modeling best practices throughout the organization. Present results of model performance and continually strive to optimize performance through best practices techniques, additional data sources and transformation of data into actionable business intelligence. Develop and implement exception reporting. Assist with the analysis and documentation of strategic initiatives. Provide support in the design, implementation and analysis of ad hoc requests. Abide by approved budget. Other duties as assigned.

5 years credit portfolio risk management or modeling Bachelor's Degree in Business, Economics, Mathematics or related area Advanced experience in data mining and statistical analysis Experience with Python, R, SQL, Snowflake or other similar data mining and analysis tools, Demonstrates understanding of the credit profitability model and life cycle Demonstrates strong decision making aptitude including credit scoring to drive decisions Demonstrates understanding and utilization of various statistical analysis methodologies including regression analysis, gradient boosting, Kolmogorov Smirnov (KS), Divergence or other similar tests Demonstrates ability to extract, manipulate and validate quality of data from multiple data sources Demonstrates business acumen with an ability to challenge existing methodologies and process Demonstrates strong analytical skills and the ability to solve complex problems by interpreting data and results and to present in a non technical manner Demonstrates strong knowledge of champion/challenger (test/control) methodologies Demonstrates excellent verbal, written and interpersonal skills Demonstrates ability to be a self starter and work independently Demonstrates advanced proficiency of MS Excel, SQL, Powerpoint and Word

Compensation Range:

The posted compensation range on this listing represents UMB’s standard for this role, …