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The Balance Sheet Management Sr. Analyst is a seasoned professional role responsible for the development of statistical models and tools used in IRRBB and treasury, applying in-depth knowledge in data processing, visualization, analysis tools, econometric forecasting, and Interest rate risk management. The role includes developing models for balance sheet management and is subject to heightened regulatory scrutiny. Responsibilities include model development, governance, analytical skills, stakeholder management, and team interactions.
Job Responsibility:
End-to-end development and governance and support of models in treasury/IRRBB space
End-to-End model development including econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes such as Net Interest Income, Non-Interest Revenue, Interest Rate Exposure, Economic Value Sensitivity, and others
Applies analytical thinking and knowledge of statistics/modeling/data analysis tools and methodologies
Reviewing and timely submission of model documentations to Model Risk Management and other stakeholders
Develop and maintain a comprehensive modeling system ensuring consistent approach to data quality and modeling methods, audit, back test, tracking, annual validation
Present technical matters meaningfully to align with Model Risk Management on modeling and validation practices
Build key relationships with finance and business teams
Create a culture of accountability and strict quality control of the data integrity and modeling processes
Requirements:
8+ years of relevant statistical modeling/econometrics experience in financial domain
PG/Masters/PhD in quantitative discipline such as Statistics, Economics, Mathematics, or related discipline is preferred
Certifications such as FRM, CFA is a plus
Experience in developing econometric models and deep understanding of statistical techniques such as Linear Regression, Logistic Regression, Time Series, Panel Regression, Error Correction Models, Seemingly Unrelated Regression and Cointegration and Machine Learning Techniques
Working experience with Artificial Intelligence/Machine Learning techniques and packages
Hands-on experience in programming and modeling using Python and related packages
Working knowledge of statistical packages like SAS/R is a plus
Experience with SQL and databases
Experience in Excel VBA is a plus
Domain knowledge and experience in PPNR, Fixed Income Securities, Mortgage Modeling, Deposit Modeling, Asset Liability Management, Interest Rate Risk, Capital Planning
Broad understanding of financial products, accounting principles, investment, accrual products and corporate finance concepts
Excellent presentation skills
Demonstrated analytical skills including the ability to synthesize quantitative and qualitative data to draw conclusions and assist on decision making
Ability to build key cross functional and cross business relationships
Assume informal leadership roles within team
Team management skills and ability to manage multiple projects and deadlines
Nice to have:
Certifications such as FRM, CFA
Working knowledge of statistical packages like SAS/R
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