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- Tasks: Build scalable Python tools for ML models and optimise portfolios.
- Company: A cutting-edge quantitative trading firm with strong backing and a fresh approach.
- Benefits: Enjoy a clean-slate environment with real ownership and no legacy systems.
- Why this job: Join a dynamic team at the forefront of machine learning and trading innovation.
- Qualifications: Passion for coding in Python and an interest in finance or machine learning.
- Other info: No CV needed to apply; reach out directly for more info!
The predicted salary is between 43200 - 72000 £ per year.
This quantitative trading firm is backed by experienced founders and strong capital, and they’re now expanding their platform to drive their ML strategies.
You will work directly with researchers - building scalable Python tools to deploy models, working on portfolio optimisation, and driving monetisation across the stack.
It’s a clean-slate environment: no legacy, no silos, and real ownership. If you’re someone who prefers to build the machine itself rather than be a part of it, you’ll have the chance to help define how research becomes alpha.
Want to be at the intersection between machine learning and systematic trading? Apply or reach out directly at megan@saragossa.io. No up-to-date CV required.
Quant Developer - shape systematic trading employer: Saragossa
Contact Detail:
Saragossa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Developer - shape systematic trading
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and systematic trading. Being able to discuss recent advancements or tools in these areas during your conversation can really set you apart.
✨Tip Number 2
Showcase your Python skills by working on personal projects or contributing to open-source projects related to quantitative finance. This hands-on experience will demonstrate your ability to build scalable tools, which is crucial for this role.
✨Tip Number 3
Network with professionals in the quantitative trading space. Attend relevant meetups or webinars where you can connect with researchers and developers, as personal connections can often lead to job opportunities.
✨Tip Number 4
Prepare to discuss how you would approach portfolio optimisation and monetisation strategies. Having a clear understanding of these concepts and being able to articulate your ideas will show that you're ready to take ownership in this clean-slate environment.
We think you need these skills to ace Quant Developer - shape systematic trading
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Quant Developer. Familiarise yourself with concepts like machine learning, portfolio optimisation, and systematic trading to tailor your application effectively.
Highlight Relevant Skills: In your application, emphasise your experience with Python and any relevant tools or frameworks you've used in quantitative trading or machine learning. Be specific about projects where you've built scalable tools or optimised portfolios.
Showcase Ownership and Initiative: Since the role offers real ownership, illustrate instances where you've taken initiative in previous projects. Discuss how you've contributed to building systems from scratch or improved existing processes.
Craft a Compelling Cover Letter: Even though an up-to-date CV isn't required, a strong cover letter can set you apart. Use it to express your passion for the intersection of machine learning and trading, and explain why you're excited about the opportunity to shape their platform.
How to prepare for a job interview at Saragossa
✨Showcase Your Python Skills
As a Quant Developer, you'll be building scalable Python tools. Be prepared to discuss your experience with Python, including any relevant projects or tools you've developed. Highlight your ability to write clean, efficient code and how you've used Python in quantitative finance or machine learning.
✨Understand Machine Learning Concepts
Since the role involves driving ML strategies, brush up on key machine learning concepts and algorithms. Be ready to explain how you would apply these techniques to systematic trading and portfolio optimisation. Demonstrating a solid understanding of ML will set you apart from other candidates.
✨Discuss Ownership and Initiative
This firm values real ownership and initiative. Prepare examples from your past experiences where you took charge of a project or contributed significantly to a team effort. Emphasise your ability to work independently and how you can contribute to shaping their platform.
✨Prepare Questions About Their Strategies
Engage with the interviewers by asking insightful questions about their current ML strategies and how they envision the future of systematic trading. This shows your genuine interest in the role and helps you understand how you can fit into their vision.