At a Glance
- Tasks: Design and develop robust Python systems for analytics and trading platforms.
- Company: Dynamic firm at the forefront of quantitative finance and technology.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Join a talented team and make a real impact in the trading world.
- Qualifications: Strong Python experience and a passion for software engineering in quantitative 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 employer: Mint Selection
Join a forward-thinking organisation that values innovation and collaboration, where as a Senior Python Software Engineer/Quantitative Developer, you will play a pivotal role in shaping the future of analytics and trading platforms. Our dynamic work culture fosters continuous learning and professional growth, offering opportunities to lead impactful projects while working alongside talented quantitative analysts and data scientists. Located in a vibrant area, we provide a supportive environment that encourages creativity and excellence, making us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer/Software Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with professionals 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
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 production-grade systems. Share specific examples of projects where you’ve implemented strong software architecture and maintained code quality.
Tailor Your Application:Don’t just send a generic CV! Tailor your application to reflect the skills and experiences mentioned in the job description. We love it when candidates connect their past work to our needs, especially in quantitative and data-intensive domains.
Demonstrate Your Team Spirit:We’re all about collaboration here at StudySmarter. In your application, mention how you’ve worked closely with analysts or data scientists in the past. Show us that you can bridge the gap between research and engineering while keeping the team’s goals in mind.
Keep It Professional Yet Personal:While we appreciate professionalism, we also value personality! Let your unique voice shine through in your application. Share your passion for software engineering and how you approach challenges, especially in high-stakes environments like trading.
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 past work at the ready.
✨Understand the Role's Context
Familiarise yourself with the energy markets and trading systems mentioned in the job description. Knowing how your role as a Quantitative Developer fits into the bigger picture will show that you’re not just a coder but someone who understands the business impact of your work.
✨Prepare for Technical Questions
Expect to dive deep into software architecture and code quality discussions. Prepare to explain your approach to system design, error handling, and logging. They might also ask about your experience with unit and integration testing, so be ready to share specific examples.
✨Show Your Collaborative Spirit
This role involves working closely with quants and data scientists, so highlight your teamwork skills. Share experiences where you’ve successfully collaborated across teams, especially in turning research models into production-grade systems. They’ll want to see that you can bridge the gap between research and engineering.
