Data Scientist, Credit Risk Analytics

Summary

Prosper is a leading fintech company focused on personal finance and peer-to-peer lending. They are seeking a Data Scientist for their Credit Risk Analytics team to build and deploy machine learning models that enhance credit risk strategies and business decisions.

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 (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

• 2-3+ years of work experience in fintech, finance, or another high-impact field applying statistical and machine learning predictive techniques
• Consumer lending experience in unsecured personal loans or credit cards is a strong plus
• Advanced degree (M.S./Ph.D.) preferably in statistics, computer science, engineering, physical sciences, economics, or a related technical field
• Expert knowledge of statistical programming languages (e.g., Python) and database languages (e.g., SQL)
• Solid understanding of coding best practices, model documentation, and ML ops principles
• Strong communication skills with the ability to translate complex technical subject matter into clear, actionable business strategies for cross-functional partners and senior management
• Strong ability to collaborate seamlessly with people across various functions (engineering, product, compliance) and build strong relationships
• Ability to work unsupervised in a fast-paced environment, effectively prioritizing among parallel technical and strategic projects
• Ability to innovate within regulatory guidelines with a strong commitment to reproducible research and model governance
• Self-motivated, results-oriented, enthusiastic, and a creative thinker who bridges the gap between data science and business strategy

Qualifications

Must Haves

• 2-3+ years of work experience in fintech, finance, or another high-impact field applying statistical and machine learning predictive techniques
• Consumer lending experience in unsecured personal loans or credit cards is a strong plus
• Advanced degree (M.S./Ph.D.) preferably in statistics, computer science, engineering, physical sciences, economics, or a related technical field
• Expert knowledge of statistical programming languages (e.g., Python) and database languages (e.g., SQL)
• Solid understanding of coding best practices, model documentation, and ML ops principles
• Strong communication skills with the ability to translate complex technical subject matter into clear, actionable business strategies for cross-functional partners and senior management
• Strong ability to collaborate seamlessly with people across various functions (engineering, product, compliance) and build strong relationships
• Ability to work unsupervised in a fast-paced environment, effectively prioritizing among parallel technical and strategic projects
• Ability to innovate within regulatory guidelines with a strong commitment to reproducible research and model governance
• Self-motivated, results-oriented, enthusiastic, and a creative thinker who bridges the gap between data science and business strategy

Benefits

• Prosper will consider for employment qualified applicants who are non-s and will provide sponsorship.
• A 401(k) with a 5% company match
• Flexible time off
• Paid parental leave
• An annual wellness allowance
• Comprehensive health coverage
• Udemy access
• Childcare assistance
• Pet insurance
• Additional savings through Beneplace
• Digital-first tools and intentional culture