Risk Manager at Zopa
London, GB
Zopa is a lending and borrowing exchange where real people sidestep the banks to get a better deal. It's a smarter, fairer and altogether more human way of managing your money, where borrowers get a great rate and flexible terms and lenders get a great return. More than 63,000 people have loaned over £1.5 billion through Zopa since our launch in 2005 and we've been voted 'Most Trusted Personal Loan Provider' in the Moneywise Customer Awards for the past 7 years in a row.

We're looking for a Risk Manager to join our Risk Analytics team that's in charge of driving step-change improvements in credit performance by developing risk models, testing hypotheses and monitoring portfolio trends. The Risk Analytics team is responsible for credit risk strategies spanning the entire customer lifecycle from Application and Fraud Prevention to Existing Customer Strategies, Collections and Recoveries.

A Risk Manager at Zopa will work with cross-functional teams including; sales, data science, product and IT to develop and drive growth strategies, influence strategic decisions and identify new opportunities through the application of leading-edge analytical techniques. It's a team made up of bright individuals with analytical capabilities, who can translate numbers into business opportunities and deliver insights to drive decision-making.

A successful Risk Manager at Zopa should have the following attributes:
Extensive experience in a Risk Analysis role
Experience of managing and mentoring junior colleagues, and delivering on projects
A degree in any quantitative field (Business, Maths, Economics, Finance, Statistics, Science or Engineering)
Conceptual thinking – ability to find innovative ways to solve analytical problems
The ability to provide insight from data, assessing the commercial / financial impact and recommending actions
Ability to consistently deliver accurate, error-free results to a high standard within tight deadlines
Excellent oral and written communication skills with ability to translate insight into a coherent story that drives action
Very good SQL or SAS skills
Desirable but not required
Good programming ability with either Python, R, Scala, Java or Matlab data science context (either creating propensity models, segmentations or solving complex problems using optimisation techniques)