Senior Data Scientist, Model Risk Management
Oportun (Nasdaq: OPRT) is a digital banking platform that puts its 1.9 million members' financial goals within reach. With intelligent borrowing, savings, budgeting, and spending capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $15.5 billion in responsible and affordable credit, saved its members more than $2.3 billion in interest and fees, and helped our members save an average of more than $1,800 annually. For more information, visit Oportun.com.
WORKING AT OPORTUN
Working at Oportun means enjoying a differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture where we all feel a sense of belonging and are encouraged to share our perspectives. This inclusive culture is directly connected to our organization's performance and ability to fulfill our mission of delivering affordable credit to those left out of the financial mainstream. We celebrate and nurture our inclusive culture through our employee resource groups.
- 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.
- Conduct independent testing on AI/ML models.
- 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 the 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.
- Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline.
- 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.
- 3+ years of experience leveraging machine learning methodologies, such as GBM, XGBoost, and NLP etc.
- Excellent writing and communication skills.
- Good team player and willing to help and share.
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