Job Description Summary
Responsible for ensuring that the method employed for risk measurement and management is financially sound. The Quantitative Analyst will be will be responsible for assessing new modeling methodologies for implementation in the risk management practice and provide opinion on modeling and risk management of banking and derivative products. Actively involved in researching and modeling non-maturity deposit behavior.
Essential Job Functions
The Quantitative ALM Analyst will be responsible for:
- Performing data analysis and developing models (statistical models, Machine Learning algorithms…) to forecast customer behavior across a variety of deposits and loan products: exercise of the prepayment option embedded in loans, decay profiles and repricing models for deposits, drawdowns of credit lines…
- Supporting and maintaining existing models which include data gathering, data analysis, model performance monitoring and testing, impact analysis on risk metrics, and addressing model validator, auditor, or regulator concerns
- Contributing to the team technological watch by preparing memos, presentations, and documentation of research and analysis based on academic papers, new modeling technics (Machine Learning algorithms…), Big Data environments…
- Providing quantitative support to other Treasury ALM teams
- Working closely with model validation and other Treasury ALM analysts
- Bachelor's degree in a quantitative field, and 5 to 8 years of experience in statistical modeling or Master's or PhD degree in a quantitative field, and 5+ years of experience in statistical modeling
- Requires advanced knowledge of job area typically obtained through advanced education combined with experience.
- May have practical knowledge of project management.
- Bachelor's Degree in a quantitative field; Math, Statistics, Finance or Economics - Required
- Master's Degree or PhD in a quantitative field; Math, Statistics, Finance or Economics - Preferred
- Understanding of Treasury Asset Liability Management, Interest Rate Risk and Liquidity risk is desired as well as knowledge of financial products
- Strong data compilation, programming skills and qualitative analysis skills (knowledge of SQL preferred)
- Strong statistical modeling background based on technical training or advanced education in a quantitative field
- Advanced knowledge of various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies, using SAS, R, Python or similar statistical package. Knowledge of some Machine Learning algorithms is a plus
- Possess strong written and verbal communication skills
- Must be able to write in a technical matter to clearly document model development process
- Demonstrated independence, team work and leadership skills
- Strong project management skills
Equal Employment Opportunity Policy
Bank of the West is an Equal Opportunity employer and proud to provide equal employment opportunity to all job seekers without regard to any status protected by applicable law. Bank of the West is also an Affirmative Action employer - Minority / Female / Disabled / Veteran.
Bank of the West will consider for employment qualified applicants with criminal histories pursuant to the San Francisco Fair Chance Ordinance subject to the requirements of all state and federal laws and regulations.