Quantitative Developer - Python
£600 - £700 a day
Our clients Global Markets Quantitative Research division is in charge of the modelling, pricing & risk management developments for the entire offering of products within the Global Markets activity. The team operates globally with representatives in London, Paris, Asia and New York and plays a critical role in providing innovative solutions.
They require a strong and permanent cooperation with trading and the Global Markets IT division to ensure all quant developments integrate optimally with the IT ecosystem, thereby ensuring the best deliveries to the business.
THE ROLE EXPLAINED
The setup requires the calculation of specific COC and MPU reserves on all market parameters (swap or spread curves, volatilities, FX etc.):
COC: Close Out Cost based on average historical bid offer
MPU: Market Parameter Uncertainy based on historical stdev of mid prices
This calculation is currently done manually with a huge number of spreadsheets and is extremely costly in terms of operation. Hence the Global Markets Quant Research team has been tasked with industrializing the value setup to reduce the operating cost.
The role is therefore to implement this industrialization in an efficient way:
Automate as much as possible the data gathering (some are simple while other like bbg chats are more complex to process)
Automate the calculation using scripts techniques
Grouping of similar reserves methodologies together to reduce number of calculation scripts
Deliver this full industrialized chain for the RiskGM analyst responsible for the calculation
Essential skills / Systems ( Incl. languages & previous experience required)
Data retrieval (Bloomberg, Reuters et.)
Data manipulation and storage (SQL etc.)
Proficiency in scripting languages (python etc.)
Desirable skills / Systems
A quant background is useful but not essential given that some value methodologies for advanced parameters have a quantitative model behind them.
Ability to work under pressure (tight deadline for the project)
Ability to work in teams given the strong interaction between Quant Research and Risk teams to push this project forward.
Ability to explain and communicate given that the Risk teams will have to be accompanied during the testing and transition phase.
The project involves using and manipulating data from multiple sources, this will need a reactive, flexible and agile approach.
Posted by Morgan McKinley, 15 Feb