Data Scientist, Credit Risk Analytics
P
ProsperFintech Credit Risk
United StatesFull-TimeMiddle
Salary$129,000 - $179,000 a year
Apply NowOpens the employer's application page
Job Details
- Experience
- 2-3+ years
- Required Skills
- PythonSQLMachine LearningMLOps
Requirements
- 2-3+ years of work experience in fintech, finance, or another high-impact field applying statistical and machine learning predictive techniques.
- Advanced degree (M.S./Ph.D.) in statistics, computer science, engineering, physical sciences, economics, or a related technical field.
- Expert knowledge of statistical programming languages (Python).
- Expert knowledge of database languages (SQL).
- Solid understanding of coding best practices, model documentation, and ML ops principles.
- Ability to innovate within regulatory guidelines.
- Strong commitment to reproducible research and model governance.
- Strong communication skills with the ability to translate technical subject matter into actionable business strategies.
- Ability to work unsupervised in a fast-paced environment and prioritize parallel projects.
Responsibilities
- Build industry-leading machine learning models for managing credit and fraud risks.
- Collaborate closely with engineering to deploy models into a production environment.
- Leverage complex data sources to develop credit and fraud strategies to improve performance and optimize risk decisions.
- Propose and execute strategic solutions to complex business problems.
- Analyze ad-hoc portfolio performance and conduct root-cause analysis.
- Develop internal tools and workflow solutions to increase productivity.
- Monitor credit risk models and strategies in production.
- Assess the validity of new machine learning algorithms and features.
- Conduct high-impact, ad-hoc analyses supporting risk management, operations, and corporate development.
View Full Description & ApplyYou'll be redirected to the employer's site
