VP Model Risk Management

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Location
Salt Lake City, UT
Job Type
Direct Hire
Date
Mar 16, 2017
Job ID
2462425

Vice President, Model Risk Management, Salt Lake City, UT. Relocation is Available for this position.

The Company is headquartered in Salt Lake City, Utah and is an FDIC insured, Utah state chartered bank.  The Company is a leading national provider of online consumer and small business loans made in partnership with finance companies, OEMs, retailers and financial technology companies.

Job Summary - The VP – Model Risk Management position will report to the Chief Credit Officer for the Bank and will support all Credit related initiatives undertaken.

Primary Responsibilities
Develop and implement statistical and machine learning based quantitative models used in underwriting strategies, loss forecasting and capital calculations
Analyze existing strategic partner programs from credit risk standpoint and drive asset management strategies
Drive new partner deals risk evaluation of programs
Develop and drive analysis of portfolio health through modeling as well as valuation techniques to drive best investment decisions
Develop alternative model approaches to assess model design and advance future capabilities
Review and assess model validation plans and processes
Assess the risk model methodologies, outputs, and processes and work with various Industry leading Fintech lending partner and retail partners associated with the bank
Understand relevant business processes and portfolios associated with model use
Understand technical issues in econometric and statistical modeling and apply these skills toward assessing model risks and opportunities
Plan and manage validation projects, manage model inventories and model governance process
Communicate clearly and concisely both verbally and through written communication via model validation reports and presentations
Present methodologies and Validation process and techniques to Regulators
Required Skills and Experience
Master’s degree in Statistics, Economics, Mathematics, Industrial Engineering, Operations Research, Financial Engineering, Physics, Engineering or Computer Science
At least five years’ experience in quantitative analysis with statistics or data mining
Extensive prior experience in consumer lending based modeling
Able to both develop analysts and work in matrix organization
Proficiency with statistical and data software languages and packages including SAS, R , Knowledge Seeker and E Miner
Familiarity with machine learning techniques such as GBM, Random Forest and ensembles of multiple nested regression techniques
Strong verbal and written communication skills