🚀 The Job

• You will develop innovative risk strategies for new products - given our goal of being present at every point a $ touches a start-up, our goal is to launch new products to support our customers through their lifecycle.
• You will develop a portfolio level view, perform sensitivity analyses, and use that information to drive portfolio strategy going forwardYou will support step-change improvements in credit performance by connecting drivers of credit trends to historical behavior, and testing hypotheses using business, data and statistical analysis.
• You will have a deep and intuitive understanding of credit risk, and develop approaches to mitigate losses, responsibly grow revenue, and monitor performance of strategies and portfolio.
• You will perform analytics to assist in underwriting, improve our ability to assess risk, and increase efficiency through automation
• You will work collaboratively with data science to design new risk and valuation models and build new tools by preparing datasets, providing business insights and ensuring that the models can be leveraged in the credit policy.
• The goal is to collaborate to harness the power of data and combine it with your credit risk expertise to build lending products that will change the way recurring revenue companies think about their financial decisions.
• You will come up with alternative, less orthodox ways of looking at risk, that allow us to underwrite faster and more accurately. Consistent and structured approaches shouldn’t necessarily be at odds with thinking outside the box. We want you to be critical.
• You will collaborate with the Go to Market team bringing the learnings from the discovery process to drive origination within our risk appetite. Unlike other organisations, the Go to Market and Risk teams at Capchase are not pulling in opposite directions.

🧠 The Requirements

• Bachelor’s degree in a quantitative subject (Finance, Accounting, Engineering, Mathematics/Physics, Business, etc.).
• 5+ years’ experience with financial services/risk.
• Strong analytical and quantitative skills.
• Experience working with technical teams composed of data scientists, and other cross-functional stakeholders.
• Experience using SQL, and proficiency in Microsoft Excel.
• Extremely eager to learn and to constantly improve credit policy and the underwriting process.

💡 Extra Credit

• MBA from a top school
• Experience using Python, and Linear / Logistic Regression and/or other statistical techniques.
• Experience analysing SaaS/recurring revenue companies.
• Familiarity with SaaS metrics and business model.