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Credit Risk Manager

2 months ago

New York, United States Capchase Full time

Capchase, recognised as one of Fast Company's Most Innovative Companies of 2023, empowers SaaS companies to grow faster through access to capital & revenue management tools. We have been acknowledged by Forbes North America's best startups and also featured among Forbes Next Billion-Dollar Startups 2023. To carry out our mission, we've received $700M+ in equity and debt funding from some of the best fintech investors QED (Nubank, Klarna), 01 Advisors (Tipalti, Master Class), Bling Capital (Airtable, Gitlab, Lyft, Square), SciFI (Stripe, Brex), Caffeinated (OpenDoor, Airtable).

In a little over three years, we've provided billions in funding to thousands of companies, expanded operations to ten countries in the US and Europe, and grown our team from four co-founders in May 2020 to 130 Capchasers today.

Since our launch in 2020, we've achieved several milestones:

4K+ companies registered

5,000 plus months additional runway generated

Over 120 Capchasers working across 14 cities around the world representing over 20 nationalities

10 countries in which we operate

250% annual company growth

Built an awesome culture.

We are looking for a talented and motivated Portfolio Manager to continue building the world's best fintech risk team. As a Portfolio Manager, you will report to the VP of Risk, and will be responsible for shaping the credit policy for new and existing products, developing strategies to grow the portfolio in a risk-sensitive manner, and testing hypotheses using data analysis. You will also collaborate very closely with the data science team to quickly and iteratively evolve our predictive capabilities.

You'll work alongside exceptional professionals. The Risk team at Capchase is responsible for underwriting, pricing and portfolio monitoring while being supported by an incredibly talented Data Science team.

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.


We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.