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- Tasks: Design and implement AI-driven trading strategies in a fast-paced environment.
- Company: Global proprietary trading firm at the forefront of AI and machine learning.
- Benefits: Competitive salary, access to cutting-edge technology, and real P&L ownership.
- Other info: Collaborate with top experts and access high-frequency datasets for innovative trading.
- Why this job: Make a real impact in finance by leveraging advanced AI and ML techniques.
- Qualifications: 2-5 years in quant trading or AI/ML research; strong programming skills required.
The predicted salary is between 36000 - 60000 £ per year.
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
Opportunity:
- Join a global leader in systematic and algorithmic trading with a strong London presence
- Be at the intersection of finance, AI, and technology with real P&L ownership
- Access to high-frequency datasets, scalable computing power, and proprietary research tools
- Collaborate with top AI scientists and quantitative researchers globally
Algorithmic 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 Algorithmic Trader – AI & Machine Learning Strategies
✨Tip Number 1
Network like a pro! Connect with professionals in the trading and AI/ML space on LinkedIn or at industry events. Don't be shy to reach out for informational chats; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI/ML in trading. 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 algorithms. Practice coding challenges and be ready to discuss your past projects in detail. Confidence in your abilities can set you apart from the competition!
✨Tip Number 4
Apply through our website! We’ve got a range of exciting opportunities that align with your skills. Plus, it’s a great way to get noticed by our hiring team directly. Don’t miss out on your chance to join us!
We think you need these skills to ace Algorithmic 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 role of Algorithmic Trader. 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 algorithmic trading and how your background in AI and machine learning makes you a perfect fit for our team. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any interesting projects related to trading strategies or machine learning, don’t hold back! Include links to your GitHub or any publications that demonstrate your expertise and creativity.
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 this exciting opportunity in our growing London hub!
How to prepare for a job interview at Flynn and Chase
✨Know Your Algorithms
Make sure you brush up on your knowledge of AI and machine learning algorithms, especially reinforcement learning and deep neural networks. Be ready to discuss how you've applied these techniques in past projects or research.
✨Showcase Your Coding Skills
Since advanced programming skills are crucial for this role, practice coding problems in Python or C++. You might be asked to solve a problem on the spot, so being comfortable with coding challenges will give you an edge.
✨Understand the Market
Familiarise yourself with current trends in financial markets, particularly in equities, FX, and commodities. Being able to discuss recent market movements and how they relate to algorithmic trading will demonstrate your passion and insight.
✨Prepare for Collaboration Questions
This role requires a collaborative mindset, so think about examples from your past where you've worked effectively in a team. Be ready to discuss how you bridge research with real-world trading impact, as this will show your ability to contribute to their dynamic environment.