Risk Modeler I

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 or machine learning predictive techniques such as logistic regression, ARIMA-style models, decision trees, gradient boosting, or other algorithms. They should be familiar with common software tools for statistical analysis, such as SAS, Enterprise Miner, R, Python, or H2O. 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

• Perform complex analyses and modeling that maximize profits or asset growth and minimize credit losses or other risk exposures.
• Serve as an expert consultant to senior management on highly complex issues.
• Manage the deployment of new models and the live testing or pilot programs derived from them.
• Monitor ongoing model performance to ensure stability and efficacy.
• Anticipate issues based on knowledge of business trends and propose direction and solutions.
• Provide peer review for other analysts within the team.
• Research the impacts of business decisions.
• Partner with technology groups to define business requirements.
• Provide analytic support to ensure the company goals are met.
• Perform other duties as assigned.

Position Requirements

• 4 year degree in quantitative area such as statistics, economics, mathematics or finance – or a minimum of 2 years of college-level business or statistical classes plus equivalent industry experience.
• Excellent statistical and quantitative skills.
• Excellent communication skills, both written and oral.
• Excellent analytic and conceptual problem-solving skills.
• Advanced capability with at least one of the following: SAS, Enterprise Miner, R, Python,
• Well-developed organizational and prioritization skills, with the ability to manage multiple and sometimes competing priorities.
• Flexibility and ability to thrive in a fast-paced, rapidly changing environment.
• Proficiency with Microsoft Office.

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.