Support trading platforms and financial applications for the Asset Management Technology Solutions team.
Locations (4)
London, England, United Kingdom
Birmingham, England, United Kingdom
Edinburgh, Scotland, United Kingdom
Telford, England, United Kingdom
Compensation
Up to £41,000, discretionary bonus, private medical cover, 38 days annual leave, excellent pension, life assurance, career breaks, income protection, volunteering days, and more.
Responsibilities
Provide first‑line support for trading and financial applications such as BlackRock Aladdin, Bloomberg, Tradeweb, and other platforms.
Lead engineering for complex eTrading features, modernize front office platforms, architect low latency systems, and drive technical excellence across global teams.
Compensation
$122,000.00 - $200,000.00 annualized salary, offers to be determined based on experience, education and skill set.
Responsibilities
Define and lead engineering approach for complex features
Design technology tool stack and evaluate new testing tools
Enable CI/CD capabilities for teams
Guide design and best practices for high code performance
Provide end-to-end delivery of complex features
Requirements
Bachelor Degree or Equivalent Professional Experience
Nice to have: AI assisted software development tools
Design, build, and maintain proprietary in-house databases and data infrastructure to support systematic credit trading activities and develop algorithmic trading strategies.
Compensation
Receive a highly competitive salary with performance-based bonuses
Responsibilities
Design, build, and maintain proprietary in-house databases and data infrastructure to support systematic credit trading activities.
Develop, implement, and continuously enhance algorithmic trading strategies across cash bonds, CDS, indices, ETFs, and other credit products.
Establish and manage an independent two-sided algorithmic market-making and trading book across DM and EM credit markets.
Research, develop, and deploy multi-factor quantitative models to identify trading opportunities and generate alpha within systematic credit strategies.
Requirements
Advanced degree in Quantitative Finance, Mathematics, Statistics, Physics, Engineering, Computer Science, or a related quantitative discipline.
Nice to have: cloud-based data and computing environments
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