A technology driven consumer lending firm is looking to build out their fraud analytic team as they transition to an entirely digital platform. This position would be using the latest in machine learning technologies to develop fraud identification and prevention engines for their installment lending platform. Reporting directly into the head of data science, this role would have strong senior leadership exposure while driving automation across all of their loan products.
Responsibility:
- Lead the development and implementation of fraud risk models across each segment of the loan life cycle including: underwriting, decision and payments.
- Develop data pipelines to be prepared for rapid learning
- Partner with data and machine learning engineering teams to implement and optimize machine learning technology.
- Effectively report findings to senior leadership and directly influence changes within the business.
- Communicate and manage relationships with third party vendors
Requirements:
- Master's or PhD in any STEM related field (Statistics, Applied Mathematics, Computer Science, etc.)
- 5+ years of data science experience, preferably within the lending domain.
- Proficient in leveraging machine learning techniques such as Gradient Boosting, clustering, logistic regression and neural networks.
- Proven track record working with cloud computing tools such as: AWS EMR, Spark, etc.
- Excellent Written and verbal communication skills.
