Quantitative Credit Risk Analyst

Creditspring; London; On-site; GBP 35,000 - 65,000; Full time

Job description

We are Creditspring, a new way of borrowing that focuses on its members and provides them with safe and efficient short-term financial products.

We're a fast-growing FCA-regulated consumer credit company. We have members, not customers, and we take a lot of pride in that!

As one of the UK’s only subscription finance companies in the market, we truly have a unique value proposition. Our mission is very clear: to improve the financial stability and resilience of our members. We do this through the products we provide, the partnerships we have, and our educational content. We want our members, and everyone in the UK, to be able to better manage their finances and steer them away from high-cost, unregulated credit options.

About the role

Working within the Underwriting (Data Science) team, you will be instrumental in supporting the company’s ability to assess credit risk, optimise product offerings, and have the opportunity to advance your data science skills.

Sitting at the intersection of Data, Engineering, Operations, Product, and Marketing, the role is critical to support further platform growth and product innovation.

The role is suited to a well-rounded candidate, with strong project management skills and an analytical mindset. It offers an opportunity to develop and deepen data science, business, and system analytics skills.

Responsibilities

Credit risk analytics:

• Business partner to other teams to assess feasibility and support various growth initiatives, designing and implementing acquisition, product, and lending strategies.
• Lead end-to-end reviews of incoming queries related to the decisioning process and onboarding journeys – producing recommendations and making data-driven decisions.
• Investigate and explain performance trends using SQL skills and knowledge of the systems.
• Communicate insights and findings effectively to stakeholders.

Project and process management:

• Coordinate change processes related to the credit lifecycle - from idea generation, project management to deployment and monitoring.
• Maintain up-to-date documentation and log of the changes.
• Quality assurance, including code review, pre and post-deploy testing, and long-term post-deploy monitoring.

Performance monitoring and analytics:

• Monitor decisioning funnel performance and suggest continuous improvements to the decisioning checks.
• Exceptions monitoring, reporting team and company KPIs and OKRs.
• Create monitoring dashboards and promote to company-wide MI tools.
• Data lead on the external API feeds used in decisioning – credit reference agencies, open banking data providers, and other providers.

What you'll need to succeed

• 2+ years of prior experience in credit risk analytics, preferably within an SME or retail lending environment.
• Solid knowledge of Python for data extraction, transformation, and analysis.
• Experience with statistical inference and supervised machine learning stack (scikit-learn, pandas, numpy, jupyter).
• SQL proficiency in manipulating, merging, and cleaning or checking data from multiple sources including internal data and external feeds.
• Demonstrated success in analytics delivery - via presentations, reports, and BI dashboards.
• Strong communication skills, with the ability to explain complex concepts to non-experts.
• Ability to work independently and collaborate within cross-functional teams.
• Comfortable working in a fast-paced and ever-changing work environment.
• Willingness to take on a broad range of tasks outside of the “core role”.

Don’t meet all the listed requirements? Research shows that women and people of underrepresented groups often don't apply for jobs unless they're 100% qualified. As an equal opportunities employer, we know that diversity is a key part of our teams' successes - so if your experience doesn’t fit perfectly but this role excites you, we’d love for you to apply. We’re committed to Creditspring being an inclusive environment where employees feel welcomed, valued, and listened to; we want you to thrive as your true self.

Please note that the People Team is contactable only via [e-mail]. Unsolicited emails to other team members will not be actioned.