Harrington Starr
Quant Software Engineer
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Quantitative Developer (Python)
We are partnering with a global financial technology organisation that builds optimisation platforms used by leading financial institutions to reduce risk, improve capital efficiency and solve complex large-scale optimisation problems.
This team develops high-performance Python applications that combine software engineering with mathematical optimisation. The work is engineering-first, with an emphasis on building robust production systems rather than pure quantitative research.
The Role
We're looking for a mid-level Quantitative Developer / Financial Engineer to join a collaborative engineering team responsible for developing and enhancing large-scale optimisation platforms.
You'll work closely with software engineers, quantitative specialists and product teams to design, build and support production systems that process complex datasets and deliver optimisation solutions for clients operating in global financial markets.
This is a hands-on engineering role where you'll spend the majority of your time writing production Python, improving platform performance and developing new functionality, while gaining exposure to optimisation techniques used to solve real-world financial problems.
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Typical projects include
- Enhancing optimisation algorithms to support new business requirements
- Developing new functionality within Python optimisation services
- Improving runtime performance and scalability of core optimisation platforms
- Building reliable data pipelines and analytics components
- Supporting production optimisation runs and improving operational resilience
- Streamlining workflows through automation and improved system architecture
Responsibilities
- Design, develop and maintain Python applications supporting optimisation services
- Build and improve optimisation and analytics libraries
- Work with large datasets and optimise data processing pipelines
- Collaborate with engineering and product teams to deliver high-quality software
- Support production systems and investigate performance improvements
- Contribute to architectural discussions and continuous improvement initiatives
- Write clean, well-tested and maintainable code
What they're looking for
- Around 3–5 years' commercial Python development experience
- Strong software engineering fundamentals
- Experience working with NumPy and Pandas
- Experience building production software within data-intensive or numerical environments
- Strong problem-solving ability
- Comfortable working with complex technical challenges
- Excellent communication skills
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Any experience in the following would be advantageous:
- Linear Programming
- Mixed Integer Programming (MIP)
- Convex Optimisation
- Operations Research
- Gurobi, OR-Tools, Pyomo or similar optimisation libraries
- Financial markets, derivatives or risk systems
- Linux or AWS environments
- Mathematics, Physics, Engineering or Computer Science background
The ideal profile
This role would suit someone who enjoys writing high-quality Python and solving mathematically interesting problems.
It is not a pure Quant Research position. The successful candidate will be an engineer first, with enough mathematical understanding to work with optimisation models and numerical algorithms.
A background in financial markets is beneficial but not essential, provided you have strong software engineering skills and a solid foundation in mathematics.
The team offers a collaborative environment where engineers have ownership of their work, contribute to product direction and solve technically challenging problems with real-world impact.
Contact Ciara Clarke at Harrington Starr for a confidential discussion on this role.
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