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Financial Institutions - Quantitative Analyst - Analyst - London
January 9, 2018
London, United Kingdom
Fitch's Financial Institutions (FI) Group is a market leader with the highest penetration of global issuer rating coverage among peers.
We are looking for an ambitious data scientist or quantitative analyst to join our 'Special Projects Group (SPG)' an integral part of Fitch's global FI group. Based in London the SPG is a team of specialist resources dedicated to the provision of high quality data and quantitative analytics to Fitch's global FI rating teams. In particular the SPG focuses on broad thematic areas such as risk modelling, stress testing and regulation but also acts as the focal point between the rating group and centralised functions such as IT, Compliance and Operations.
The candidate will be required to perform a range of data science and risk analysis tasks in the global FI space, which range from small scale but rapid data analytics to the development and delivery of sophisticated solutions. Additionally, the candidate will also be responsible for delivering enhanced data automation and visualisation capabilities to the team, and contribute to various ongoing statistical modelling activities.
Key tasks and responsibilities are:
Core data science tasks, including:
Collecting, cleaning and aggregating data,
Statistical analysis and interpretation,
Data exploration, visualization and presentation,
Management of local data and databases,
Automation of all of the above
Contribute to the proto-typing, implementation, deployment and support of the team's upcoming tactical and strategic risk modelling and data analytics.
Develop detailed understanding of the existing proprietary tools, models and processes, and progressively take on responsibility for support and enhancements.
Provide ad-hoc data analytics for the wider FI analytical teams as necessary, plus contribute to any technical training/demonstrations as necessary.
Develop a broad understanding of bank credit analysis and key industry developments.
Qualifications and Experience:
Prerequisite: A good educational background to at least first university degree level in a data science or quantitative subject (eg mathematics/physics/engineering)
Beneficial: Further academic studies (completed or planned) in the area of risk management or quantitative finance.
Prerequisite: A high level of competency or fluency in R and Excel/VBA. A good knowledge of statistical techniques for data analysis. Excellent data visualization skills.
Beneficial: 1 - 2 years prior data science and/or finance industry experience.
In a relatively small team the successful candidate will need to be able to work independently, at times to tight deadlines, and be able to manage a mix of short and longer-term timetables. Good written and verbal communication skills are required.