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    Financial Assets Modeler Sr - Middlesbrough, United Kingdom - Flagstar Bank

    Flagstar Bank
    Flagstar Bank Middlesbrough, United Kingdom

    2 weeks ago

    Default job background
    Full time
    Description
    Position Title

    Financial Assets Modeler Sr

    Location

    Ohio Corporate Office (Cleveland, OH)

    Job Summary


    JOB SUMMARY

    A Senior Financial Assets Modeler is responsible for the design, build and operation of compliant quantitative models and producing analytics for current expected credit loss ( CECL ), macroeconomic scenarios ( Stress Testing ), and portfolio ( Loan Concentration ) credit risk.

    Design and assist with the integration of all applicable inputs, outputs, calculations and analytics required by the Assets and Liabilities Management ( ALM ) and the Allowance for Loan and Lease Losses ( ALLL/CECL ) models.

    The scope of model design and operation includes development, enhancement, maintenance, and execution of statistical and cash flow models; design, creation, testing and reporting of macroeconomic scenarios; support for governance, benchmarking, management, validation, and regulatory reporting pertaining to quantitative models; and the development, enhancement, maintenance, and execution of production control procedures within the integrated ALM/CECL/Stress Testing model frameworks.

    A Senior Financial Assets Modeler is responsible for maintaining the skills and knowledge relevant to their assigned job responsibilities.

    In addition, the Modeler promotes and advocates the adoption of appropriate new methodologies for quantitative models and analysis that benefit the Bank.

    Provides assistance with identifying and designing quantitative solutions to problems as presented by management to further the Bank's strategic plans.

    This role may provide coaching or mentoring to other members of the department.

    Job


    Responsibilities:

    ESSENTIAL FUNCTIONS
    Performs extensive data analysis in support of financial planning, stress testing and reporting.

    Develops, tests, and documents internally developed quantitative models and analytics, including complex financial, econometric, and statistical frameworks primarily focused on risk management and financial reporting.

    Implements, tests, and documents externally developed and/or licensed models.

    Assists with the integration of models within the FMA Department and amongst other Bank departments to ensure consistency and accuracy across all model outputs.

    Develops, tests, and documents complex model execution procedures and controls to be run in an audited, production environment. Develops, tests, and documents procedures and controls for executing external, third-party models. Assists with the development and implementation of routine analytics and reports. Utilizes industry standard quantitative software, data science programming languages, database systems, and workstation productivity applications to produce required deliverables.

    Assists with the creation of management and regulatory reports containing descriptions of the development, testing, validation and execution of quantitative modeling and analytic outputs.

    Ensures compliance with model governance policies and procedures as an integrated feature of all quantitative modeling and analytic activities.

    Performs model governance procedures including the execution of required production controls; model, data and procedure version control; and end-user computing policies and guidelines.

    Assists with the analysis and documentation of Management, Internal Audit, Enterprise Risk Management and Regulatory findings and requirements. Assists with departmental cross-training and knowledge transfer to minimize staffing risk and promote effective communications. Performs special projects and additional duties and responsibilities as required.

    Where applicable and when performing the responsibilities of the job, employees are accountable to maintain Sarbanes-Oxley compliance and adhere to internal control policies and procedures.



    EDUCATION AND EXPERIENCE
    Bachelor's degree in Finance, Economics, Statistics, Mathematics or other advanced quantitative field. Master's or Ph.
    D. preferred.

    5 to 8 years of experience with credit risk modeling; including linear modeling frameworks (Ordinary Least Squares, Logistic Regression, Generalized Linear Models, Credit Risk Scorecards, Time Series, Roll Rate, Transition Matrix, etc.).

    5 to 8 years of experience with commercial lending data; Commercial Real Estate (CRE), Commercial and Industrial (C-I), Construction, and Asset-Based Lending (ABL).

    5 to 8 years of experience working with and analyzing model data preparation requirements (missing values, transformations, re-classifications, etc.). 3 to 5 years of experience with CCAR/DFAST modeling requirements. 1 to 3 years of experience with ALLL/CECL modeling requirements. 1 to 3 years of experience deploying credit loss models into a production ALM environment. 1 to 3 years of experience using third-party macroeconomic forecast data.

    KNOWLEDGE,


    SKILLS AND ABILITIES

    SAS:

    experience developing and documenting well-structured, standards-based SAS programs using Enterprise Guide, SAS data analysis and management procedures (Base SAS procedures, SAS macros, SAS functions, program factoring such as include , etc.), PROC SQL, statistical procedures (PROC GLM, PROC GEE, PROC GENMOD, PROC LOGISTIC, PROC ARIMA, etc.).


    R:
    experience using similar routines mentioned above with RStudio and standard R, additional R experience developing transition matrix models


    Excel:
    experience developing and documenting well-structured, auditable workbooks, credit risk calculations, pivot tables, and publishable tables, charts, and graphs


    SQL:
    experience developing and running complex data extract and transformation queries using SAS' PROC SQL. Experience working in a SQL Server database environment. Experience working in a SAS Server environment using Enterprise Guide as the development and execution environment. Experience working with various data file formats including SQL databases, SAS, Excel, and raw format data. Experience working in a networked Microsoft Windows end-user computing environment.
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