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So if you’re enthusiastic by the idea of accessing cutting edge technology & innovation to make an impact, why don't you join us?
As a Business Support Analyst you will be responsible for executing regular month end and quarter end processes. The processes are required to meet regulatory commitments such as the Month End Stress and Quarterly Model Parameter Update. Each process requires Risk Analytics to be configured to use unique inputs so that results can be produced and distributed to stakeholders. You will be required to confirm the correct inputs (such as Equity Collateral Haircuts), agree a schedule, Configure Risk Analytics, Monitor Risk Analytics Runs, verify the output and distribute the results. To be successful in this role you will need hands-on skills such as Excel, SQL, editing files (XML, CSV, JSON), monitoring log files, executing jobs using command line and Autosys.
- Documenting and executing month-end and quarter-end processes
- Configuring and executing Risk Analytics
- Distributing results to downstream consumers
- Responding to business enquiries, performing analysis and prioritizing enquiries
- Suggesting changes for enhancement to the regular processes
- Degree level education
- Good written and spoken English
- Good MS Excel and SQL skills
- Knowledge of editing XML, CSV and JSON files
- Comfortable with Windows Operating System, executing batch processes
- Knowledge of Investment Banking Risk Management would be an asset
Project is about development and support of the risk management platform used for calculating bank's counterparty risk exposure and allowing this to be hedged. The system consumes trades and market data from systems all over the bank and all asset classes, then runs a series of complex risk calculations across the entire trade portfolio and provides feeds to downstream systems of the results. The system needs every trade in the bank before it can run any calculations, and some of these trades are extremely complex products.
The system's purpose is to provide risk reports to groups across the bank as well as external regulators. It is not strictly an end-user application but has circa 100 users consuming its results and working with its UI components. The system must deal with large volumes of incoming data in different formats, with a combination of real-time and daily input feeds. Calculations are extremely large scale and are distributed across a compute grid of few thousand CPUs.
