Data Scientist

3 - 6+ years of work experience in fintech, finance, or other high impact fields applying statistical and machine learning predictive techniques Consumer lending experience in unsecured personal loan or credit card is a plus Advanced degree (M.S./PhD) preferably in statistics, computer science, engineering, physical sciences, economics, or related technical field Expert knowledge in one of the statistical programming languages such as Python Expert knowledge in database languages such as SQL Solid understanding of coding best practices and model documentation Strong communication skills Strong interpersonal skills Ability to work unsupervised in fast-paced environment and prioritize among parallel projects Ability to think within regulatory guidelines with a mindset toward reproducible research

Build industry-leading machine learning models for managing credit and fraud risks Leverage multiple complex data sources to optimize approve/decline and credit line assignment decisions Collaborate with engineers to deploy models into a production environment Propose and execute solutions to various problems within business constraints Use responsible AI techniques following regulatory requirements and lending best practices Help the team with developing tools and workflow solutions to increase data science productivity Actively monitor the credit risk models in production Extract the most value out of data to significantly impact business metrics Assess the potential usefulness and validity of machine learning algorithms and features Conduct ad-hoc analysis related to risk management, investor services, operations and corporate development