At a Glance
- Tasks: Design and develop robust Python systems for analytics and trading platforms.
- Company: Join a leading firm in the energy and trading sector.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship and career advancement opportunities.
- Why this job: Make a real impact by optimising trading systems with cutting-edge technology.
- Qualifications: Strong Python skills and experience in quantitative or data-intensive domains.
The predicted salary is between 60000 - 80000 € per year.
We are seeking a Senior Python Software Engineer/Quantitative Developer to take a leading role in the design, development, and evolution of the client’s core analytics and trading platforms. The role is explicitly Python‑centric, with a strong focus on software architecture, code quality, and reliability across complex quantitative systems. You will work embedded within the analytics and trading function, partnering closely with quantitative analysts and data scientists to turn research models into robust, production‑grade Python systems. The role is intended to complement a mathematically strong team by bringing deeper software engineering rigour, helping scale both the codebase and the organisation as trading activity grows.
Responsibilities
- Design, implement, and maintain production‑grade Python systems supporting:
- Power price forecasting pipelines
- Optimisation and dispatch of flexible assets (BESS, gas, hydro)
- Trading, simulation, and backtesting environments
- Establish and uphold strong Python engineering standards across the analytics codebase, including:
- Clear package and module structure
- Well‑defined interfaces between models, data, and execution layers
- Consistent error handling, logging, and observability
- Lead improvements in test coverage and reliability, spanning unit, integration, and regression testing for quantitative models
- Proactively identify, prioritise, and shape platform enhancements that most effectively support the trading roadmap, balancing urgency, technical debt, and cross‑team impact in close collaboration with analytics, trading, and product stakeholders
- Work closely with quants to refactor research‑driven Python code into maintainable, extensible components without compromising model fidelity
- Optimise performance‑critical Python code paths, including efficient use of vectorisation, parallelism, and memory management
- Collaborate with DevOps and Data Engineering on deployment, CI/CD, and runtime monitoring of Python services and batch workflows
- Provide technical leadership and mentorship on Python best practices, raising the overall engineering maturity of the analytics team
Required Skills and Experience
- Strong professional experience as a Python software engineer, working on large or long‑lived codebases
- Deep understanding of Python for production use, including:
- Packaging, dependency management, and environment isolation
- Testing frameworks and test design for numerical code
- Profiling and performance optimisation in Python
- Solid grounding in software engineering fundamentals, including:
- System and API design
- Code readability, maintainability, and extensibility
- Version control and collaborative development workflows
- Experience working in quantitative, scientific, or data‑intensive domains
- Ability to operate comfortably at the interface between research, engineering, and commercial use cases
Desirable Experience
- Experience in energy markets, commodity trading, or financial systems
- Familiarity with optimisation libraries, numerical methods, or simulation frameworks in Python
- Exposure to containerisation, cloud‑native Python deployments, or distributed compute patterns
- Prior experience modernising or hardening research‑oriented Python codebases
Personal Attributes
- Strong engineering judgement with a pragmatic approach to complexity
- Comfortable taking ownership of critical systems used in live decision‑making
- Motivated by applying high‑quality software engineering to problems with tangible commercial and system‑wide impact
- Able to challenge constructively and influence technical direction without over‑engineering
Quantitative Developer/Software Engineer in London employer: Mint Selection
As a leading employer in the financial technology sector, we offer a dynamic work environment where innovation and collaboration thrive. Our commitment to employee growth is evident through continuous learning opportunities and mentorship from industry experts, particularly in our vibrant location that fosters creativity and teamwork. Join us to be part of a mathematically strong team, where your contributions directly impact trading strategies and analytics, all while enjoying a culture that values quality engineering and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer/Software Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a GitHub profile showcasing your Python projects, especially those related to quantitative analysis or trading systems. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding key concepts in software engineering. Practice common algorithms and data structures, and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your experience with Python and quantitative systems to stand out from the crowd.
We think you need these skills to ace Quantitative Developer/Software Engineer in London
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your experience with Python in your application. We want to see how you've tackled complex problems and built robust systems. Share specific examples of projects where you’ve implemented best practices in Python, especially in production environments.
Keep It Clear and Concise:When writing your application, clarity is key! Use straightforward language and avoid jargon unless it’s relevant. We appreciate a well-structured application that gets straight to the point, showcasing your skills and experiences without unnecessary fluff.
Tailor Your Application:Don’t just send a generic application! Take the time to tailor your CV and cover letter to our job description. Highlight your experience in quantitative domains and any relevant projects that align with our needs. This shows us you’re genuinely interested in the role.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Mint Selection
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around production use. Be ready to discuss packaging, dependency management, and testing frameworks. They’ll likely want to see how you handle performance optimisation, so have some examples of your work handy.
✨Understand the Role's Context
Familiarise yourself with the energy markets and trading systems. Knowing how your role fits into the bigger picture will help you answer questions more effectively. It’s also a great way to show your enthusiasm for the industry and the specific challenges they face.
✨Showcase Your Engineering Judgement
Be prepared to discuss your approach to software architecture and code quality. They’ll want to know how you balance urgency with technical debt. Bring examples of past projects where you’ve made critical decisions that had a significant impact on the system or team.
✨Prepare for Technical Leadership Questions
Since this role involves mentoring and leading improvements, think about how you’ve influenced teams in the past. Have stories ready about how you’ve raised engineering standards or helped colleagues with best practices in Python. This will demonstrate your ability to take ownership and drive change.
