Phi PartnersPhi Partners has been a trusted capital markets consultancy for more than 20 years, providing quantitative and technology expertise across front office, pricing and risk.
We support more than 80 financial institutions across the buy-side and sell-side through niche capabilities spanning quant, engineering, vendor platforms and cloud infrastructure.
Our teams work on complex, real-world problems across models, analytics, applications, data and cloud infrastructure, within an international delivery organisation built around regional hubs and specialist centres of excellence.
For people who enjoy technically demanding work in capital markets, Phi offers the opportunity to work closely with expert colleagues and major financial institutions on high-value, business-critical initiatives.
About The Programme Our client’s Risk Engine group oversees the Credit and Market risk exposures and stress calculation systems across asset classes which the bank trades in. Responsible for design, development and level 3 support of this risk calculation platform, the Risk Engine group operates on a global scale within the bank’s Risk & Capital Technology department.
The client is in the process of launching a business-critical project replacing a current legacy stress testing application with a new system. This includes adding stress testing functionality to the existing Market Risk platform and carefully decommissioning the legacy system. This is a mission critical project for the bank’s business, and as such Phi is looking to on-board an experienced Python Developer as a Technical Consultant to support our client on this risk and capital management technology transformation project, focusing on innovative technologies and always striving to meet the business objectives.
Role & Responsibilities The consultant will be working closely with the business stress testing, development, and analytical teams to understand the business requirements and work towards replacing the legacy application. Main responsibilities will include getting into Python code, blending it together to be run under single scenario, building various algorithms, along with investigating and explaining differences in results between the legacy and newly developed systems.
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