Data Scientist, Underwriting

Example projects

• Training a quantile regression model to forecast the distribution of SMB revenues and precisely size our financing offers
• Using LLMs to help build a risk model and forecast that lets us underwrite merchants on banking transaction data
• Performing risk-based pricing optimization and experimentation
• Collaborating with engineering to build a modular real-time underwriting system
• Building a simulation platform to model and evaluate conversion and risk exposure across varied configurations for our financing offers
• Ingesting new data sources from both 3rd parties and partner platforms, and evaluate their use in improving our risk predictions

Beyond these focus areas, our team helps expand our impact by recruiting exceptional talent, improving our tools, and supporting each other through regular seminars and project reviews.

About YouYour Impact

You will make an outsized impact on Parafin’s trajectory by leading projects from end to end. You will quickly learn new methods, apply them across diverse areas of the business, and implement them robustly. You will develop expertise in specific areas of the business, but may tackle projects across domains as our priorities evolve.

You’ll own the full data-science lifecycle, from research to deployment, to power our underwriting engine. Specifically, you will:

• Design, train, and deploy production underwriting models
• Design experiments and metrics to drive risk and pricing decisions
• Partner with engineering and product teams to architect automated underwriting systems
• Identify business opportunities to improve growth and profitability via improvements to our underwriting posture

Your Background and Skills

We are open to candidates from a variety of academic backgrounds and professional experiences. We believe the most effective data scientists bring the following skills to their work:

• Statistical Reasoning
• Approach data analysis with a critical, intellectually honest eye
• Design concise metrics that guide decision making
• Employ robust experimental design and causal inference methods
• Develop valid and predictive machine learning models
• Business Acumen
• Identify and effectively prioritize business problems
• Solve business problems using appropriate data science techniques
• Anticipate the impact of your work on our financial performance, customers, and compliance obligations
• Engineering Mindset
• Write legible, reliable, and tested code
• Build or source tools to boost the team’s efficiency
• Architect technical systems that are highly scalable, reliable, and observable
• Leadership and Collaboration
• Model Parafin’s values of efficiency, intellectual honesty, accountability, and empathy
• Build trusted relationships with stakeholders
• Document work, seek feedback, and share learnings proactively
• Focused Execution
• Prioritize high-impact use of your time
• Scope projects rigorously
• Act with urgency