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Lead Analyst

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Company: Aquinas Consulting

Location: Stamford, CT

Date Posted: July 25, 2014

Source: Rekrutr.com

Lead Analyst 1 - Modeling

Role Summary :

Support initiatives related to quantitative analytic modeling of the lifecycle of a commercial credit risk analytics. Serve as the data analyst for model governance, model development, and model deployment activities.

Responsibilities :

Support a Quantitative Methodology leader in developing and implementing holistic process for statistical modeling in credit risk analytics and credit stress testing analytics (design, development, validation, calibration, documentation, approval, implementation, monitoring and reporting) in (PD, credit transition of cumulative PD, LGD, EAD, etc.)

Support a Quantitative Methodology leader on formulating and evaluating alternative credit risk methodologies or econometric credit stress testing specifications for conceptual soundness and stakeholders' model requirements.

Assist in statistical analysis to help research and gather underlying credit modeling dataset.

Assist in new modeling sensitivity development and impact timing analysis as required by HQ Enterprise Stress Testing's procedure; and update the analysis annually.

Develop econometric and analytic models to be ...

Lead Analyst 1 - Modeling

Role Summary :

Support initiatives related to quantitative analytic modeling of the lifecycle of a commercial credit risk analytics. Serve as the data analyst for model governance, model development, and model deployment activities.

Responsibilities :

Support a Quantitative Methodology leader in developing and implementing holistic process for statistical modeling in credit risk analytics and credit stress testing analytics (design, development, validation, calibration, documentation, approval, implementation, monitoring and reporting) in (PD, credit transition of cumulative PD, LGD, EAD, etc.)

Support a Quantitative Methodology leader on formulating and evaluating alternative credit risk methodologies or econometric credit stress testing specifications for conceptual soundness and stakeholders' model requirements.

Assist in statistical analysis to help research and gather underlying credit modeling dataset.

Assist in new modeling sensitivity development and impact timing analysis as required by HQ Enterprise Stress Testing's procedure; and update the analysis annually.

Develop econometric and analytic models to be used by EFS Capital Planning team for credit stress testing processes.

Conduct wing-to-wing advanced statistical robustness tests on regression specifications, coefficients and residual errors; and feedback into model development improvement and regression specification changes.

Conduct analytics to validate the performance of existing quantitative risk models, recommend changes, and support gap closing projects. Performance evaluation includes outcome analysis, back-testing analysis and benchmarking analysis.

Support model review and validation requirements; and support model remediation strategies and multi-generation plan.

Lead modeling data capture, gathering, mastering and maintenance in support of modeling databases

Manage model supporting data warehouses in terms of accuracy and completeness; understand data and process structures from System of Record to ensure accuracy and precision of data used for modeling, reporting and analysis.

Drive standardization of processes that ensure timely generation and retrieval of reporting and risk analytics data, including support of model management framework.

Qualifications :

Bachelor's degree in quantitative related field (Economics, Finance, Math/Stat, Engineering, Operations Research, etc.) with 3+ years of relevant Risk, Finance, or graduate research experience.

Graduate degree in Statistics or applied Economics (for limited dependent, categorical or cross-sectional regressions),

Demonstrated experience in statistical model lifecycle management, including proficient level of expertise with at least one statistical modeling language/utility (Matlab, Stata, R, SAS or equivalent) proficiency and expertise building and implementing routines for data transformation, such as logistic regression, multinomial regression, Cox hazard modeling.

Demonstrated strong SQL skills and experience delivering SQL code and supporting physical database designs

Strong knowledge of MS office tools, and data mining tools (Access, SQL, BO, SAS, etc.)

Strong business finance acumen, especially in Financial Services Industry

Characteristics :

FRM and CFA a plus Familiarity with Basel Initiative, Treasury operations and regulatory matters

Experience in management of, or results driven contribution to, cross-functional teams (Risk, Finance, IT, Operations)

Demonstrated ability to lead and support projects from beginning to end Self-starter, ability to work independently in a fast paced environment and deliver solid action oriented results quickly

Operational understanding of and experience with Model Risk, and balancing sophistication with simplicity (Ockham's Razor) Excellent oral and written communication skills

Strong interpersonal and team management skills

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