At a Glance
- Tasks: Join our team to enhance systems for large-scale financial optimisation.
- Company: Dynamic financial tech firm focused on innovation and collaboration.
- Benefits: Competitive salary, professional growth, and a supportive team environment.
- Other info: Collaborative culture with opportunities for continuous learning and improvement.
- Why this job: Make a real impact in finance while developing your quantitative and software skills.
- Qualifications: 3-5 years Python experience, strong problem-solving skills, and a passion for data.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- 3-5 years of experience using Python in a data-intensive or numerical environment
- Familiarity with software development practices such as testing, version control, and clean code design
- Experience working with libraries such as pandas and numpy
- Strong problem-solving skills and an interest in understanding how systems behave
- Ability to communicate technical ideas clearly to a range of audiences
- Desirable: Optimisation techniques (e.g., linear programming, mixed-integer programming, convex optimisation)
- Desirable: Experience with optimisation libraries or modelling tools
- Desirable: Understanding of financial products, derivatives, or risk concepts
- Desirable: Exposure to UNIX/Linux or cloud environments such as AWS
- Desirable: A background in mathematics, statistics, or related fields
What the job involves
We are looking for a mid-level quantitative developer / financial engineer to join our optimisation services team. In this role, you will contribute to building and enhancing systems that power large-scale optimisation runs used by global financial institutions. You’ll collaborate with colleagues in Software Engineering and Product Development to deliver reliable, high-quality solutions, while continuing to develop your expertise in quantitative methods and software engineering.
This is a product and client-focused role, where successful candidates will develop one or more of our services and will support live client optimisations. This is a collaborative role with opportunities to contribute both to strategic projects and continuous improvements, where your work will have visible and meaningful impact.
- Implement improvements to our Interest Rates LCH Compression algorithm
- Enhance our Counterparty Risk optimisation with new constraints and features
- Work on adding support for Hedge Funds and Clearing Brokers in Initial Margin optimisations
- Improve runtime performance of our core algorithms
- Streamlining workflows and improving system architecture to reduce manual steps
- Contribute to the development and improvement of optimisation and analytics libraries
- Work with teammates to understand and improve how data flows through our systems
- Support optimisation runs alongside our Production team, helping ensure reliable execution
- Explore ways to tune models and solutions to better meet client needs
- Take part in both longer-term projects and shorter, iterative improvements
- Collaborate with colleagues across teams to share knowledge and improve our products
You’ll work in a collaborative, supportive team where knowledge sharing is encouraged. You’ll have opportunities to learn and deepen your expertise in both quantitative methods and software engineering. You’ll be involved in solving real-world problems with tangible impact on financial markets. We value continuous improvement - both in our systems and in how we work together.
Quantitative Developer employer: London Stock Exchange
The London Stock Exchange is an exceptional employer, offering a dynamic work environment that fosters collaboration and innovation. With a strong focus on employee growth, we provide ample opportunities for professional development and career advancement, all while being part of a prestigious institution located in the heart of London. Our inclusive culture values diverse perspectives, ensuring that every team member can contribute meaningfully to our mission of driving brand impact and achieving outstanding results.
