Assistant Manager - Investment Banking - Edinburgh

Assistant Manager (SAS Visual Analytics) - Investment Banking - Edinburgh

I am working with one of the world's biggest banks, who are undergoing significant transformation across multiple business areas. The role available for an Assistant Manager role sits within the Regulatory Compliance Analytics function which is responsible for developing descriptive analytics and predictive models to support the regulatory compliance function.

Their aim is the management and monitoring of customer conduct risks across the banks business lines and sites. Due to the nature of the work going on within the business, this role will give the successful candidate exposure to a range of market leading technologies that have only recently been introduced to the business and not currently being used by many competitors.

The essential skills/requirements for this role are as follows:

- Good experience of working in a risk and analytics function, ideally within a large banking organisation previously
- Define compliance metrics and design/deploy MI dashboards to provide insight into customer conduct issues. Execute the assigned projects/analysis as per the agreed time lines and with accuracy and quality
- Support the definition and build out of the conduct risk framework.
- Quantitative analysis experience.
- Extract and analyse data through the use of SAS software (ideally SAS VA), SQL or other data management tools, from core systems.
- Develop predictive models using traditional statistical modelling, machine learning or behavioural analytics techniques

It would be desirable is candidates had the following experience:

- Experience and Exposure to visualisation technologies such as Qlikview/Spotfire/Tableau will be an added advantage
- Extensive experience in a relevant analytics field. Knowledge and understanding of conduct risk, as well as investigative and/or behavioural analytics experience is preferred.
- Knowledge of statistical techniques and working experience of SQL, SAS, Matlab or Python.
- Graduation/Post Graduation degree in Statistics, Mathematics, Economics on any other quantitative discipline considered a significant advantage

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