Overview

　　The Quantitative Risk Model Developer will primarily focus on supporting model development and Big Data/Machine Learning initiatives. The role will also support the development and implementation of digitally driven credit risk management strategies to optimize performance across the credit life cycle. The individual will be a key member of the Automated Decisioning team responsible for the strategic vision of automated decision making and digital risk management strategies to transform the way small businesses access financing.

　　The individual will work with cross-functional teams, including business development, sales, credit, IT, and model governance functions, to develop and drive innovative digital lending strategies, influence strategic decisions, and identify new opportunities through the application of leading-edge analytical techniques. The individual will have highly developed analytical capabilities with the ability to translate data and analysis into business opportunities and deliver insights to drive optimized growth strategies that are balanced against risk.

　　Responsibilities

　　Building and supporting models for Commercial BankingBuilding and supporting models for regulatory requirementsBuild tools & process enhancements and identifying opportunities to automate parts of model development and contribute to infrastructure, tool, or process improvement to enable efficiencies on the team.Ad-hoc quantitative support for other areas in the organizationQualifications

　　Basic Qualifications:

　　Bachelor's degree and 4 years of experience or a HS Diploma/GED and 8 years of experience.3 years of experience developing/validating statistical and financial modelsPreferred Qualifications:

　　Master's degreePreferred area of study: quantitative finance, Applied Mathematics, Statistics, Engineering, or other quantitative-oriented disciplines.Experience successfully collaborating with others in a change driven environment, particularly technology, internal controls, and project management teams.Demonstrated ability to effectively organize tasks, manage time, set priorities and deadlines.Strong quantitative skills and analytical problem-solving ability.Functional with database development, maintenance, and extraction of dataAdvanced programming skills in one of the following - R, SAS, MATLAB, or PythonKnowledge of Model Risk Management Regulatory Guidance (SR 11-7/OCC 2011-12)Experience in CECL/DFAST environment is desirable.Excellent written and verbal communication and interpersonal skills, including the ability to reach the best possible results without compromising the work quality.Understand technical issues in statistical modeling, including theoretical assumptions and methodology limitations, data pitfalls, model sensitivities, simulation approaches or scenario analyses for low-default portfolios, and applying these skills toward providing robust solutions to business problems.