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at Webster Bank
200 Executive Blvd South-HF433
If you're looking for a meaningful career, you'll find it here at Webster. Founded in 1935 by Harold Webster Smith, our focus has always been to put people first--doing whatever we can to help individuals, families and businesses achieve their financial goals. And while we've grown into a leading commercial bank, we remain passionate about serving our customers, supporting our communities, and making a difference in people's lives. We can make a difference in your life, too. By empowering you to build the meaningful career you've been looking for.
Responsibility, respect, trust, teamwork and citizenship are the values Webster was founded on. Together we call them The Webster Way, and they are what sets us apart as a bank and an employer. Guided by these values, we put people first. Working hard to live up to our customers, and each other, every day.
The incumbent is expected to be a key contributor in an evolving model risk management framework, working under the guidance of VP, Model Risk Manager.
The primary job function is to assist the Model Risk Manager in administering the Model Risk Management program. This includes working with model owners, IT and ERM to develop, implement and support a source code management process to monitor the model development cycle and also monitor changes to the production code of high risk in-house and third party models at an adequate frequency and depth. In case of high risk vendor models, the configuration needs to be monitored. The job function also includes testing model input data and testing of select models as the need arises. Appropriately applying the model governance policy and the documentation requirements that go with it is also one of the job functions.
The individual will be exposed to a wide variety of models and will interact with model owners and staff across Webster. The scope includes internally and externally developed consumer and commercial credit scoring models, DFAST, ALLL, BSA/AML/fraud systems, Capital/ALM models, Budgeting / FP&A models and basic derivative valuation models.
Core competency involves understanding the purpose of the model, how it works, how it is used, how well it performs, and what effective challenges are to the current model. Formal training in a quantitative discipline coupled with a verifiable understanding or background in a business environment is required.
Assist Model Risk Manager in running of the Model Risk Management program.
Implement and support a source code management process to monitor the model development cycle and also monitor changes to production code of high risk in-house and third party models at an appropriate frequency and depth.
Participate as an independent reviewer at model change management working group meetings.
Investigate and analyze the scope, nature and business implications of model production code and configuration changes for internally developed models and vendor models, respectively.
Author reports and document all changes made to production code by model owners.
Test select models and document the review and findings.
Enforce code change management issue escalation and approval authority protocol.
Develop strong relationships with key lines of business.
Quantitative background with 1-3 years of modeling/analytical experience within commercial banks or financial institutions. Skills include regression analysis and testing/validation techniques such as back-testing, bench-marking and sensitivity analysis.
Good business knowledge and familiarity with consumer/small business/commercial banking products, operations and processes.
Working knowledge of programming and relational databases (SAS, SQL, Excel/VBA).
Strong ability with standard software tools such as Excel, PowerPoint and Word.
Familiarity with model risk management best practices and regulatory guidance (OCC 2011/12 SR11-7).
Analytical, resourceful, persistent, pragmatic and motivated.
Time management skills to prioritize multiple tasks.
Model development or validation experience with DFAST and/or ALLL.
Experience with common risk tools and bank systems such as Moody's, Intex, Yieldbook, Bloomberg API.
Experience in building constructive relationships and communicating with a wide range of stakeholders.
Bachelors or Masters' degree in econometrics, statistics, data analytics or other quantitative field (e.g. physics, math, engineering, etc.). Finance or Business BS/MS/MBA with strong quantitative or programming background is also acceptable.