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- Tasks: Design and implement AI-driven trading strategies in a fast-paced environment.
- Company: Global trading firm at the forefront of AI and machine learning in finance.
- Benefits: Competitive salary, access to cutting-edge technology, and collaborative culture.
- Why this job: Make a real impact on trading with advanced AI techniques and world-class resources.
- Qualifications: 2-5 years in quant trading or AI/ML, strong programming skills, and financial market knowledge.
- Other info: Join a dynamic team with opportunities for growth and collaboration with top experts.
The predicted salary is between 36000 - 60000 £ per year.
Overview:
Our client is a global proprietary trading and investment firm leveraging advanced quantitative research and cutting-edge technology. With daily trading volumes in the billions and a growing European hub in London, the firm is at the forefront of applying artificial intelligence and machine learning to capital markets.
The team is expanding to capture opportunities in systematic, data-driven trading across asset classes. This role offers the chance to design and scale next-generation trading models in a high-impact environment with access to world-class infrastructure and datasets.
Key Responsibilities:
- Research, design, and implement trading strategies using AI/ML techniques such as reinforcement learning, deep neural networks, and natural language processing
- Develop scalable models for signal generation, execution optimisation, and risk management
- Work with large, complex, and alternative datasets to identify alpha opportunities
- Collaborate with engineers to deploy ML models into live trading environments
- Continuously monitor and refine models, adapting to market dynamics in real time
Candidate Requirements:
- 2–5 years of experience in quant trading, AI/ML research, or data-driven strategy development within a hedge fund, trading firm, or leading tech company
- Advanced programming skills (Python, C++, TensorFlow, PyTorch) with experience building ML pipelines and backtesting frameworks
- Deep knowledge of statistics, machine learning, and applied mathematics; MSc/PhD in Computer Science, Physics, Engineering, or related field preferred
- Exposure to financial markets (equities, FX, commodities, or derivatives); direct trading experience highly valued
- Entrepreneurial, collaborative mindset with ability to bridge research and real-world trading impact
- Access to high-frequency datasets, scalable computing power, and proprietary research tools
- Collaborate with top AI scientists and quantitative researchers globally
Seniority level
- Associate
Employment type
- Full-time
Job function
- Analyst
- Industries
- Investment Management
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Quant Trader – AI & Machine Learning Strategies employer: Flynn and Chase
Contact Detail:
Flynn and Chase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Trader – AI & Machine Learning Strategies
✨Tip Number 1
Network like a pro! Reach out to professionals in the quant trading space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects and trading strategies. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your programming skills and understanding of machine learning concepts. We recommend practicing coding challenges and discussing your thought process out loud during mock interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for talented individuals who are ready to make an impact in the world of quant trading.
We think you need these skills to ace Quant Trader – AI & Machine Learning Strategies
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Quant Trader role. Highlight your programming skills, AI/ML projects, and any relevant trading experience to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for quantitative trading and how your background makes you a perfect fit for our team. Don’t forget to mention specific AI/ML techniques you've worked with!
Showcase Your Projects: If you've worked on any interesting projects related to AI or machine learning, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they relate to trading strategies!
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 shows you’re keen on joining our team!
How to prepare for a job interview at Flynn and Chase
✨Know Your AI/ML Stuff
Make sure you brush up on your knowledge of AI and machine learning techniques, especially reinforcement learning and deep neural networks. Be ready to discuss how you've applied these in past projects or how you would approach designing trading strategies using them.
✨Show Off Your Coding Skills
Since advanced programming skills are a must, be prepared to demonstrate your proficiency in Python, C++, or any relevant languages. You might even face a coding challenge, so practice building ML pipelines and backtesting frameworks beforehand.
✨Understand the Financial Markets
Familiarise yourself with different asset classes like equities, FX, and commodities. Having direct trading experience is a bonus, so if you have any, be sure to highlight it during the interview. Show that you can connect your technical skills to real-world trading scenarios.
✨Be Ready to Collaborate
This role requires a collaborative mindset, so think about examples where you've worked with engineers or other teams to deploy models. Emphasise your ability to bridge research and practical applications, as this will resonate well with the firm's focus on teamwork and innovation.
