Senior Data Scientist - Credit Risk

Description

Position 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 fluent 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 and initiative 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, publishes and presents 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 anticipate 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 goals
• Performs other duties as assigned.

Position Requirements

• Advanced degree in a pure quantitative field + 5yrs experience in data science
• Excellent statistical and quantitative skills
• Excellent analytic and conceptual problem-solving skills
• Excellent written, verbal, and visual communication skills
• Advanced capability with at least one of the following: Python, R, SAS, SQL
• Well-developed organizational and prioritization skills
• Flexibility and adaptability to contribute to a driven team environment.
• Professional proficiency with standard technology

Preferred

• 5+ years experience in consumer credit risk management
• Demonstrated experience coding and publishing open-source functions/packages
• Repeated hands-on experience with predictive techniques from a broad variety of approaches, including machine learning, parametric, unsupervised, or time-series modeling
• Hands-on experience building MLOps process flows for production model deployment