Data Scientist, Credit Risk Analytics

### Your role in our mission

Prosper is seeking a Data Scientist under the Credit Risk Analytics vertical. You will become a core contributor with machine learning expertise in the credit risk team, delivering results that directly impact business value. This is a unique, hybrid role where you will not only build and deploy industry-leading predictive models but also play a critical role in shaping our credit risk strategy and business decisions. ### How you’ll make an impact

* 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 (e.g., credit bureau reports, customer-supplied information) at scale to develop credit and fraud strategies to improve the credit performance and optimize risk decisions. * Propose and execute strategic solutions to complex business problems, operating effectively within constraints and aligning with broader company objectives. * Analyze ad-hoc portfolio performance at a granular segment level on an ongoing basis. Identify trends and conduct root-cause analysis to isolate key performance drivers. Communicate findings and recommendations to the Risk Management and broader Prosper community. * Help the team develop internal tools and workflow solutions to increase data science productivity and operational efficiency. * Actively monitor credit risk models and strategies in production, extracting actionable insights to significantly impact key business metrics. * Assess the potential usefulness and validity of new machine learning algorithms and features sourced from diverse, alternative data providers. * Conduct high-impact, ad-hoc analyses supporting risk management, investor services, operations, and corporate development initiatives. ### Skills that will help you thrive

* 2-3+ years of work experience in fintech, finance, or another high-impact field apply