Senior Data Scientist - Model Risk Management

November 9

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Oportun

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Financial Services • Responsible Lending • Pre-Paid Debit Cards • Serving the Underbanked • Data Analytics

1001 - 5000

Description

• In this role you will be working on both traditional statistical modeling methods and cutting-edge machine learning models used for loss forecasting, underwriting, marketing, collection management, and fraud detection. • Conduct independent review and testing on both traditional statistical modeling methods and AI/ML models used in loss forecasting, underwriting, marketing, collection management, and fraud detection. • Perform independent model validation on the cutting-edge machine learning models and produce high-quality model validation reports, highlighting risks and limitations of the model in a concise manner. • Communicate to business audiences through verbal and written presentations describing the results of the validation findings and mitigation actions. • Work closely with business owners/model users and developers to understand the business context for model use and facilitate the model approval process. • Stay up to date with regulatory expectations of model development, use, and validation activities. • Support Oportun’s model risk management framework, including annual validation plans, model inventory, model risk ranking, and model risk governance. • Develop and maintain effective partnerships with key model stakeholders. • Support the coordination of model risk governance practices with the model users. • Attention to detail in both analytics and documentation.

Requirements

• Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline. • 3+ years of experience validating and/or developing traditional statistical modeling methods applied in loss forecasting (Time series, linear regression, logistic regression, survival modeling, etc.) • 3+ years of experience and knowledge of Fair Value (FV) Loan Loss Estimate (LLE) process and modeling. • 1+ year of experience leveraging machine learning methodologies, such as GBM, XGBoost, and NLP etc. • 3+ years of practical quantitative programming experience with Python, SQL, Spark, and/or Scala. • 3+ years of experience in financial risk model development or validation. • Excellent writing and communication skills. • Good team player and willing to help and share.