Machine Learning and Statistical Modeler

Description

Position Summary

Credit One Bank is seeking a statistical modeling professional with a curious and competitive mindset to support the organization’s strategy and goals.

This position is a part of the Risk Management department but supports the entire bank. Our modeling professionals are tasked with developing predictive models and optimization techniques for customer targeting, fraud detection, risk assessment, underwriting, credit line increases, as well as complex ad hoc analyses.

The successful candidate will have familiarity with statistical and machine learning predictive techniques such as logistic and linear regression, time series models, decision trees, gradient boosting, bagging, and other algorithms.

They should be familiar with common software tools for statistical analysis, such as SAS, Enterprise Miner, R, or Python.

And they should demonstrate the ability to follow their nose to mine insights from large databases and link their analytic conclusions with actionable recommendations for business strategy.

Summary of Essential Job Functions

• Acts as lead modeler during development cycles.
• Performs complex analyses and modeling that maximizes profits or asset growth, and minimizes credit losses or other risk exposures.
• Serves as an expert consultant to senior management on highly complex issues.
• Manages the deployment of new models and the live testing or pilot programs derived from them.
• Monitors ongoing model performance to ensure stability and efficacy.
• Anticipates issues based on knowledge of business trends, and proposes direction and solutions.
• Provides peer review for other analysts within the team.
• Researches the impacts of business decisions.
• Partners with technology groups to define business requirements.
• Provides analytic support to ensure the company goals are met.
• Performs other duties as assigned.

Position Requirements

• Master’s degree or PhD Degree in Finance, Economics, Mathematics, Statistics, Quantitative Analysis, or another technical discipline.
• 3+ years of related experience at a Financial Institution or Consulting Firm in the areas of model development
• Advanced capability with at least one of the following : SAS, Enterprise Miner, R, Python, or similar.
• Proficiency with Microsoft Office.
• Experience with Machine Learning / AI methodologies and related applications.
• Strong analytical and conceptual problem-solving skills.
• Excellent written and communication skills and ability to create and maintain quality model documentation.
• Ability to collaborate effectively and follow-up to ensure achievement of deadlines, outcomes, and results.
• Ability to work independently and self-motivate in a fast-paced and rapidly changing environment.
• Flexibility and ability to thrive in a fast-paced, rapidly changing environment.

Preferred

• Advanced quantitative degree.
• Experience with machine learning algorithms.
• 4+ years risk management or equivalent industry experience.
• Knowledge of financial analysis, credit reporting and profitability drivers.

Credit 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.