Our Story
Hello there. We’re Zopa.
We started our journey back in 2005, building the first ever peer-to-peer lending company. Fast forward to 2020 and we launched Zopa Bank. A bank that listens to what our customers don’t like about finance and does the opposite. We’re redefining what it feels like to work in finance. Our vision for a new era of banking puts people front and centre — we’ve built a business that empowers everyone to aim high, every day, to move finance forward. Find out more about our fantastic offerings at
Zopa.com!
We’re incredibly proud of our achievements and none of it would be possible without the amazing team here. It’s not just industry awards we’re winning, we’ve also been named in the top three UK’s Most Loved Workplaces.
If you embrace unconventional challenges, are unafraid to think differently and are driven to make an outsized impact, you’ll thrive here at Zopa, so join us, and make it count. Want to see us in action? Follow us on Instagram @zopalife
The role:
You will join a high performing risk analytics team responsible for assessing the credit risk of our assets across all lending products using the Expected Credit Loss framework, understanding and monitoring portfolio trends, market dynamics and macro-economic environment
Collaboration is key at Zopa which means you'll work closely with our cross-functional analytical teams including data science, product, collections and finance to develop and drive innovative approaches to calculating impairment provisions while remaining compliant with our internal policies and external regulations.
We look for bright individuals with a passion for translating numbers into business opportunities and delivering insights to drive decision-making - if this resonates with you, we'd love to hear from you!
Why join Zopa?
As a Senior Credit Strategy Analyst, you will be entrusted to lead on our most complex and highest impact projects.
You are empowered to think outside the box and devise creative, innovative solutions to the problems we tackle.
Zopa offers a broad range of lending products, including unsecured personal loans (UPL), credit cards, secured loans for the purchase of a car, and point-of-sale finance, which all pose different analytical challenges.
You work in a wider cross-functional credit, data science and finance team, so you will have the opportunity to work alongside, learn from and mentor some of the brightest minds and friendliest people in the industry!
You work with some of the best tech in the industry, such as AWS SageMaker for ML, DBT for data processing along with standard analytical tools like Python, Redshift, Tableau etc.
You gain hands-on exposure to an advanced Expected Credit Loss (ECL) framework built on cutting-edge machine learning techniques
Analysing the performance of our portfolio, identifying any areas of improvement, and recommending framework enhancements based on these findings.
Working cross-functionally to deliver end-to-end solutions and improvements.
Using advanced statistical techniques to predict customer behavior or forecast future losses
Continuously innovating on ways of working and opportunities for optimization and efficiencies across the team
Mentoring and guiding more junior team members, fostering their growth and development.
About you...
You have strong experience of solving analytical and numerical problems, preferably with experience in credit strategy or risk in a consumer lending environment.
You are familiar with the key IFRS9 modelling components (PD, LGD, EAD, Staging) (preferred)
You have a strong ability in manipulating and analyzing large datasets using SQL and/or Python
You are experienced in visualization and storytelling through data
You have a passion for translating numbers into business opportunities and delivering insights to drive decision-making with a high attention to detail
You are a structured and holistic problem-solver, and possess strong time management skills
You have an insatiable curiosity and a relentless drive to learn, improve, and share knowledge with others
You can work collaboratively with cross-functional teams, including tech, data science, finance and product