Credit One Bank
Risk Modeler II
Credit One Bank, Las Vegas, Nevada, us, 89105
DescriptionPosition Summary
Credit One Bank is seeking a statistical modeling professional with a curious and competitive mindset to join the Advanced Analytics shop. This position supports the organization’s strategy and goals from within the Risk Management department but partners with the entire bank. Our modeling professionals are tasked with projects developing predictive models, risk strategies and optimization techniques spanning all dimensions of the Bank’s credit policy, as well as delivering insights from deep dive or especially complex analyses. Project areas commonly include models or strategies for account acquisition, risk scoring, credit underwriting, loss forecasting, portfolio management, and competitive intelligence.
The successful candidate will have a technical familiarity with multiple statistical or machine learning algorithms. Those could include techniques of linear and logistic regressions, ARIMA or GARCH-style time series forecasts, exponential smoothing, tree-based methods, unsupervised learning, gradient boosting, or other algorithms. They should be skilled with common software tools for statistical analysis, such as Python, R or SAS, in addition to their skills with SQL. They should demonstrate the ability to follow their nose to mine insights from large databases, then link their analytic conclusions with actionable recommendations for business strategy.
Summary of Essential Job Functions
Performs modeling and complex analyses to maximize profits and asset returns while minimizing credit losses and other risk exposures.Engages with model users and stakeholders to deliver incremental value and bespoke solutions.Conducts live testing of strategies, models, and data attributes to evaluate benefits and propose changes to credit policy.Manages the model lifecycle end-to-end, from development through implementation, monitoring and retirement.Monitors, analyzes and publishes model performance reports to ensure stability and efficacy.Guides and reviews the technical implementation of models and strategies for live testing.Monitors, analyzes and proposes changes to risk strategies and risk management processes.Partners with strategy owners, technology groups and leaders to define and deliver on business requirements.Leverages knowledge of economic and industry trends to anticipates risks to profitability and proposes direction and solutions.Researches, quantifies, and communicates the impacts of business decisions.Acts as a consultant to business partners to provide peer review and technical guidance.Serves as an expert consultant to senior leadership on complex quantitative initiatives.Provides analytic support to drive progress toward company goalsPerforms other duties as assigned.Position Requirements
Advanced degree in a quantitative field such as statistics, economics, mathematics, or finance – or a 4yr. degree in such a field with 2 years of experience in financial services or modelingExcellent statistical and quantitative skillsExcellent analytic and conceptual problem-solving skillsExcellent written, verbal, and visual communication skillsAdvanced capability with at least one of the following: Python, R, SAS, SQLWell-developed organizational and prioritization skillsFlexibility and adaptability to contribute to a driven team environment.Professional proficiency with standard technologyPreferred
Advanced degree with 4 years of experience in a quantitative field4 years consumer credit risk management experienceFamiliarity reviewing and assessing company financial statementsBroad experience with predictive techniques from a variety of approaches, including machine learning, parametric, unsupervised, or time-series modelingFirsthand experience building at least one of the following: Risk or revenue models for consumer credit acquisitions or portfolio management strategies; Vintage-based return or loss forecasts for consumer credit products or company prospectus; Targeting models for customer acquisition campaigns; Offer-optimization algorithms for consumer credit strategies; VaR or provision for loss models; Structural macroeconometric forecastsCredit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.
Credit One Bank is seeking a statistical modeling professional with a curious and competitive mindset to join the Advanced Analytics shop. This position supports the organization’s strategy and goals from within the Risk Management department but partners with the entire bank. Our modeling professionals are tasked with projects developing predictive models, risk strategies and optimization techniques spanning all dimensions of the Bank’s credit policy, as well as delivering insights from deep dive or especially complex analyses. Project areas commonly include models or strategies for account acquisition, risk scoring, credit underwriting, loss forecasting, portfolio management, and competitive intelligence.
The successful candidate will have a technical familiarity with multiple statistical or machine learning algorithms. Those could include techniques of linear and logistic regressions, ARIMA or GARCH-style time series forecasts, exponential smoothing, tree-based methods, unsupervised learning, gradient boosting, or other algorithms. They should be skilled with common software tools for statistical analysis, such as Python, R or SAS, in addition to their skills with SQL. They should demonstrate the ability to follow their nose to mine insights from large databases, then link their analytic conclusions with actionable recommendations for business strategy.
Summary of Essential Job Functions
Performs modeling and complex analyses to maximize profits and asset returns while minimizing credit losses and other risk exposures.Engages with model users and stakeholders to deliver incremental value and bespoke solutions.Conducts live testing of strategies, models, and data attributes to evaluate benefits and propose changes to credit policy.Manages the model lifecycle end-to-end, from development through implementation, monitoring and retirement.Monitors, analyzes and publishes model performance reports to ensure stability and efficacy.Guides and reviews the technical implementation of models and strategies for live testing.Monitors, analyzes and proposes changes to risk strategies and risk management processes.Partners with strategy owners, technology groups and leaders to define and deliver on business requirements.Leverages knowledge of economic and industry trends to anticipates risks to profitability and proposes direction and solutions.Researches, quantifies, and communicates the impacts of business decisions.Acts as a consultant to business partners to provide peer review and technical guidance.Serves as an expert consultant to senior leadership on complex quantitative initiatives.Provides analytic support to drive progress toward company goalsPerforms other duties as assigned.Position Requirements
Advanced degree in a quantitative field such as statistics, economics, mathematics, or finance – or a 4yr. degree in such a field with 2 years of experience in financial services or modelingExcellent statistical and quantitative skillsExcellent analytic and conceptual problem-solving skillsExcellent written, verbal, and visual communication skillsAdvanced capability with at least one of the following: Python, R, SAS, SQLWell-developed organizational and prioritization skillsFlexibility and adaptability to contribute to a driven team environment.Professional proficiency with standard technologyPreferred
Advanced degree with 4 years of experience in a quantitative field4 years consumer credit risk management experienceFamiliarity reviewing and assessing company financial statementsBroad experience with predictive techniques from a variety of approaches, including machine learning, parametric, unsupervised, or time-series modelingFirsthand experience building at least one of the following: Risk or revenue models for consumer credit acquisitions or portfolio management strategies; Vintage-based return or loss forecasts for consumer credit products or company prospectus; Targeting models for customer acquisition campaigns; Offer-optimization algorithms for consumer credit strategies; VaR or provision for loss models; Structural macroeconometric forecastsCredit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.