Credit Risk Analyst - Fin-tech - Quant Risk

Recruiter
Harnham
Location
London, South East England
Salary
35000.0000
Posted
20 Jul 2017
Closes
19 Aug 2017
Contract Type
Permanent
Hours
Full Time

Credit Risk Analyst - Fin-tech - Quantitative
Central London
Up to £35,000 + benefits + bonus

A fast growing brand with a distinctive Fin-Tech feel is seeking a bright quantitative analyst with Credit
Risk experience and a strong academic background that will grow with the company. If you're looking for a
business that will offer you widespread exposure across various areas of FS, the opportunity to develop
both technically and commercially and become a future leader - this role is truly an exciting chance to be
part of an extremely well-respected business. This opportunity promises career progression and unrivalled
learning opportunities that will guarantee a promising trajectory for a successful career in this space.

THE ROLE

As a Credit Risk Analyst, you will be an integral part of the Credit Risk team using SAS and SQL to build
Credit Risk Models. You will be a key point of contact across the quantitative side of the business and
build on your technical skillset with the core of your role being the development of Scorecards, IFRS9,
Forecasting, Stress Testing and IRB Credit Risk models.

YOUR SKILLS AND EXPERIENCE

  • Educated to a degree level from a respected University
  • Strong commercial experience within a quantitative role within either a credit risk, marketing or wider commercial role
  • Strong technical skills having commercially utilised SAS, SQL or R
  • Confident communicator, with demonstrable experience of having delivered insight and strategy to a variety of both technical and non-technical stakeholders

THE BENEFITS:

  • £35,000
  • Competitive Benefits
  • Amazing learning opportunities
  • Career Progression
  • Exposure to full Credit lifecycle and wider commercial issues

KEY WORDS:

Credit Risk Modelling, IFRS9, Scorecards, Credit Risk Analysis, PD, LDG, EAD, SAS, R, Application, Behavioural Models, Forecasting, Quantitative Analysis