Senior Data Scientist, Model Risk Management

POSITION SUMMARY

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. The role comes with high visibility, and you will work with a variety of teams such as Data Science, Engineering, and Product Management to launch the next generation of decisioning infrastructure.  

ROLE DESCRIPTION

• 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.

REQUIRED QUALIFICATIONS

• 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.

PREFERRED/NICE-TO-HAVE SKILLS/EXPERIENCE

• Loss Forecasting or stress testing model validation experience
• AI/ML model validation experience

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