Senior Machine Learning Engineer
Senior Machine Learning Engineer
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Salary Not Disclosed
1 Vacancy
Job Description
The Role
The Risk Data Science team is looking for a Senior Machine Learning Engineer/Data Scientist to develop advanced machine learning models guide measurement strategy and data-driven decision making to support various credit risk and operational areas for SoFi Credit Card products. The person will work closely with Credit Risk Product Engineering and Operations teams to design solutions to support acquisition account management and loss mitigation. These tasks involve applying state-of-the-art machine learning methodologies deploying models into production and developing complex business rules to solve business problems. This role is very rewarding as your work will have a direct and immediate impact on the business profitability.
What Youll Do
- Develop implement and continuously improve machine learning models that support various credit and operational procedures including but not limited to underwriting account management and loss mitigation.
- Implement scalable model pipelines leveraging modern ML platforms (e.g. AWS SageMaker) and best practices in version control (Git) testing and CI/CD.
- Partner with Product and Engineering teams to operationalize models including deployment monitoring and integration into business systems.
- Collaborate with the Model Risk Management team to ensure models are developed with rigor that satisfy Model Risk Management and Governance requirements.
- Present model performance and insights to Credit Risk and Business Unit leaders.
- Explore and leverage in-house external and open-source machine learning frameworks and algorithms.
What Youll Need
- Bachelors degree in Computer Science Statistics Mathematics Physics Engineering or a quantitative field required. Masters or Ph.D. preferred.
- 3 years of relevant work experience with building implementing and deploying machine learning models.
- Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning including (but not limited to) linear regression logistic regression decision tree ensemble methods clustering outlier detection novelty detection.
- Strong programming skills in Python and SQL.
- Hands-on experience with ML model implementation in production environments using tools such as AWS SageMaker Git Docker and CI/CD pipelines.
- Effective communication skills and ability to explain complex models in simple terms.
Nice To Have
- Experience in a financial organization.
- Experience with model documentation and delivering effective verbal and written communication.
- Experience working closely with Product Engineering and Model Risk Management teams.
Required Experience:
Senior IC
Employment Type
Full Time
