Broadgate

- Research, dimension and manage the scope, nature, business implications, workflow, calendar, data, personnel and time requirements for development, implementation, and maintenance of credit loss underwriting models to support the bank’s stress-testing, regulatory reserving, and underwriting.. Lead and/or participate in Model Risk Management, Executive Management, Audit, Regulatory, and inter-departmental strategic and tactical planning & progress meetings.. - Solid knowledge of statistical theory, in particular general linear models, categorical data analysis, time series estimation, algorithmic optimization, supervised and unsupervised machine learning.. - Expert knowledge and skills in statistical programming (SAS, SQL, Python, R).. - Strong ability with standard office software such as Excel/VBA, PowerPoint, Tableaux and Word.

credit risk

Primary Responsibilities- Research, dimension and manage the scope, nature, business implications, workflow, calendar, data, personnel and time requirements for development, implementation, and maintenance of credit loss underwriting models to support the bank’s stress-testing, regulatory reserving, and underwriting.- Personally participate in the development, coding, implementation, and maintenance of models.- Develop expert knowledge and experience with Webster’s data systems and tools.- Maintain rigorous work papers during the model development process. Author reports documenting the design, development, testing and use of new models, and changes to existing models.- Develop strong relationships with Webster lines of business, Finance, Risk & IT partners, ensuring software development and support requirements are met. ? Lead and/or participate in Model Risk Management, Executive Management, Audit, Regulatory, and inter-departmental strategic and tactical planning & progress meetings.Required Skills & Experience- 5-10 years of modeling/analytical experience within a commercial bank or financial institution.- Solid knowledge of statistical theory, in particular general linear models, categorical data analysis, time series estimation, algorithmic optimization, supervised and unsupervised machine learning.- Expert knowledge and skills in statistical programming (SAS, SQL, Python, R). Experience working with complex data structures. Ability to apply methods to real-world problems.- Strong ability with standard office software such as Excel/VBA, PowerPoint, Tableaux and Word.- Good business knowledge and familiarity with commercial and consumer banking products, operations, and processes.- Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and socially intelligent.- Time management skills are needed to prioritize multiple tasks.

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