Senior Credit Risk Analyst

📋 Description

• • Lendable is at the forefront of revolutionizing consumer finance, aiming to build the world's premier technology platform that empowers individuals to access credit and manage their savings effectively. As one of the UK's rapidly ascending fintech unicorns, we have cultivated a dynamic and agile team of over 700 exceptional individuals. Our journey is marked by consistent profitability since 2017 and robust backing from esteemed investors such as Balderton Capital and Goldman Sachs. Our commitment to customer satisfaction is reflected in our outstanding Trustpilot reviews, boasting a 4.9 rating from tens of thousands of customer experiences. We have successfully re-engineered core consumer finance products, including loans, credit cards, and car finance, enabling us to disburse funds to our customers in mere minutes, a stark contrast to the days often required by traditional institutions.
• • Our ambition extends beyond our current successes. We are strategically expanding into the two largest Western markets, the UK and the US, where trillions of dollars in financial products are currently managed by legacy banking systems characterized by outdated technology and cumbersome processes. This presents a significant opportunity for disruption and innovation.
• • We are seeking a highly motivated and experienced Senior Credit Risk Analyst to join our burgeoning US Cards Credit team, known as Zable, based in Virginia. This is a pivotal new role offering a unique chance to take ownership of early-stage projects and exert substantial influence. You will collaborate closely with our talented data science, product, and engineering departments, contributing directly to the strategic direction and operational excellence of our credit card portfolio.
• • Your primary responsibility will be to contribute to the development and management of a high-performing credit card portfolio, driven by ambitious growth targets while upholding our unwavering commitment to responsible lending practices. This involves meticulously optimizing our credit decisioning processes, determining the optimal criteria for approving applicants, setting appropriate credit limits, and establishing competitive yet risk-aligned interest rates.
• • A crucial aspect of this role involves staying acutely aware of evolving economic trends and proactively adapting our credit strategies to mitigate potential risks and capitalize on emerging opportunities. You will be instrumental in developing and maintaining sophisticated models designed to forecast portfolio returns accurately and provide essential data for investor reporting, ensuring transparency and confidence.
• • You will play a key role in defining and refining credit strategies, ensuring they remain aligned with our dynamic portfolio goals and the broader objectives of the company. This requires a blend of strategic foresight and analytical rigor.
• • Leveraging your expertise in Python and SQL, you will delve into vast datasets to uncover data-driven insights that address critical business questions. This analytical work will form the foundation for informed decision-making and strategic adjustments.
• • Cross-functional collaboration is paramount. You will work hand-in-hand with product managers, engineers, data scientists, and operations teams to seamlessly implement and continuously enhance our credit strategies. This collaborative approach ensures that our strategies are not only theoretically sound but also practically executable and effective.
• • A core tenet of this role is the continuous monitoring of credit strategy performance. You will be responsible for evaluating the effectiveness of our current approaches, identifying areas for improvement, and proposing data-backed solutions to optimize outcomes and minimize risk.
• • This role offers the chance to take significant ownership, make impactful decisions from day one, and contribute to building the best technology in the industry, utilizing cutting-edge data sources, machine learning, and AI to automate and optimize processes.