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Data Scientist

Please Note: The application deadline for this job has now passed.

Job Introduction

This is an exciting and challenging position for a highly motivated and energetic individual who is looking for the next step in their career. You must enjoy working in a very fast-paced, highly flexible, dynamic environment. The role will be a Data Scientist working with many aspects of a set of consumer lending products. This position will report to the Decision Science Manager and work closely with the senior team. This is a role for a talented professional who has tremendous self-motivation, great attention to details and the ability to handle multiple requests under tight deadlines.

Based in Milton Keynes or Cardiff, this role will evolve around the development, deployment and monitoring of best-in-class models and statistical algorithms. The individual should be able to understand the business needs and use a variety of modeling techniques to deliver strong sustainable growth, within risk appetite, and to ensure best outcomes for customers.

118 118 Money is a significant financial services business offering personal loans to customers who may find it hard to get credit from their banks, but don’t want to go down the route of a payday loan. Founded in 2013, 118 118 Money came to shake up the traditional UK financial services industry with their unsecured personal loan product and has launched a credit card product in April 2018. The business is growing rapidly and is looking to bulk up on analytical capabilities to effectively support that growth.

The ideal candidate will have a very strong background in Data science and Statistics, ideally from a lending institution, with knowledge of external data sources such as Credit Bureau data. This individual will be a key member of the Analytics team.

Role Responsibility

  • Work on the creation and deployment of best in class segmented credit models that are appropriate for unsecured consumer lending products
  • Work closely with the wider Analytics team to drive improvement to the overall value of the portfolio by adapting data sources, modeling strategies, cut-offs and application processes
  • Interact with external parties such as credit reference agencies
  • Produce written summary of analysis and recommendations and present those to senior technical or non-technical audiences
  • Produce MI in order to monitor the adequacy of models already in place
  • Alert the management team of any model degradation, propose and own remediation actions
  • Work closely with colleagues across the group to deliver projects and the change agenda

The Ideal Candidate

  • Degree from a top university/college or equivalent in technical numerical field (e.g. statistics, mathematics, physics, operational research)
  • Prior experience of modelling, data science, or decision science in the context of risk management
  • Hands-on strong knowledge of data manipulation and modelling languages – SQL, SAS or R
  • Highly proficient using Excel and other analysis tools
  • Excellent verbal and written communication skills and ability to convey complex concepts to non-technical members of the team
  • Ability to work in an extremely fast paced start-up environment
  • Extremely self-motivated and ability to operate independently

 

Please be aware that should we pursue your application, all our Financial Services employees will be expected to complete a standard level CRB, adverse finance and identity check.

118 118 Money requires your personal data to process your application for a position within our Company.

If your application is successful through to telephone screening/interview, and you are not selected for a role, we may store your personal data for 3 years to enable our HR team to contact you should future roles be advertised.

Where you apply, but are not selected for telephone screening/interview, we will delete your personal data once the position is filled.

118 118 money does not use automated decisioning or profiling when selecting candidates.

For your RIGHTS under GDPR please see our Privacy Policy 

 

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