Data Scientist

Summary

Join Prosper's Data Science team as a (Sr.) Data Scientist and become a core contributor in credit risk analytics. You will build machine learning models, leverage diverse data sources, collaborate with engineers, and propose solutions within business constraints. The role requires expertise in statistical programming languages, database languages, and strong communication skills. We are open to hiring at both Senior Data Scientist and Data Scientist levels, with varying experience requirements. Competitive salaries and generous benefits are offered. Prosper is committed to an inclusive and diverse workplace.

Requirements

• 3 - 6+ years of work experience in fintech, finance, or other high impact field applying statistical and machine learning predictive techniques (educational experience taken into consideration)
• 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, and database languages such as SQL
• Solid understanding of coding best practices and model documentation
• Strong communication skills – ability to clearly and succinctly communicate technical subject matter to other team members and senior management
• Strong interpersonal skills – collaborate with people across functions and develop strong relationships
• 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
• Self-motivated, results-oriented, enthusiastic, and a creative thinker

Responsibilities

• Build industry-leading machine learning models for managing credit and fraud risks
• Leverage multiple complex data sources such as credit bureau reports and customer supplied information at large scale to optimize approve/decline and credit line assignment decisions
• Collaborate with engineers to deploy your models into a production environment
• Propose and execute solutions to various problems within business constraints
• Use responsible AI technique 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 our key business metrics
• Assess the potential usefulness and validity of machine learning algorithms and features through various data sources
• Conduct ad-hoc analysis related to risk management, investor services, operations and corporate development

Preferred Qualifications

Consumer lending experience in unsecured personal loan or credit card

Benefits

• $126,000 - $186,000 a year
• Bonus
• Generous benefits