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- Tasks: Develop and test predictive models for high-frequency trading and optimise market strategies.
- Company: Join Axon Labs, a pioneering tech firm blending neuroscience and machine learning.
- Benefits: Competitive salary, innovative work environment, and opportunities for professional growth.
- Why this job: Be a founding member shaping the future of intelligent trading systems.
- Qualifications: Postgraduate degree in relevant fields and 2-5 years of trading strategy experience.
- Other info: Dynamic role with potential to impact various industries beyond finance.
The predicted salary is between 36000 - 60000 £ per year.
At Axon Labs, we are building the DeepMind of real-time intelligence with the business model of Renaissance Technologies. We combine cognitive science, neuroscience, and machine learning to build brain-inspired prediction models that operate in real time and on the edge. Our technology is already proven in live markets, and we are focussing on high-frequency trading as the engine for long-term revenue generation. Our vision expands beyond finance to power intelligent systems that learn faster, decide better, and run more efficiently across robotics, wearables, and autonomous systems. We are hiring our first Founding Quant, a founding-level role to help design, build, and scale our research and trading platform.
Role Description
- Develop and test short-horizon predictive models and alpha signals.
- Design, implement, and optimise execution and market-making strategies.
- Build end-to-end trading pipelines, from research and simulation to deployment and live monitoring.
- Apply statistical, ML, and DL approaches to streaming time-series data.
- Take research from prototype → production → live trading across venues and instruments.
- Collaborate on real-time risk, monitoring, and control infrastructure.
Qualifications
Education
- Postgraduate degree in Mathematics, Computer Science, Physics, or Engineering from a top university.
Experience & Domain Knowledge
- 2–5 years of experience owning the full lifecycle of a trading strategy: idea generation → research → modelling → backtesting/simulation → implementation → live execution.
- Deep understanding of market microstructure, liquidity, and order-book dynamics.
- Experience in an HFT, proprietary trading, or systematic trading environment.
Technical Skills
- Strong Python skills for research, modelling, data engineering, and production workflows.
- Applied ML/DL experience in real-time time-series prediction and feature engineering.
- Ability to write clean, reliable, performance-oriented code from prototype to production.
- Proficiency in C++ for low-latency execution and optimisation.
Quantitative Trader employer: Axon Labs
Contact Detail:
Axon Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Trader
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to quantitative trading. You never know who might have a lead on your dream job or can give you insider tips on landing that role.
✨Show Off Your Skills
Create a portfolio showcasing your projects and models. Whether it's predictive models or trading strategies, having tangible examples of your work can really set you apart. Share this on platforms like GitHub or even your own website!
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python and C++ skills. Be ready to discuss your past experiences in detail, especially around the full lifecycle of a trading strategy. Practice common quantitative problems and be prepared to think on your feet!
✨Apply Through Us!
Don’t forget to check out our website for openings at Axon Labs. Applying directly through us not only shows your interest but also gives you a better chance of getting noticed. Let’s get you that Quantitative Trader position!
We think you need these skills to ace Quantitative Trader
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your technical skills, especially in Python and C++. We want to see how you've applied these in real-world scenarios, so don’t hold back on sharing your experiences!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Quantitative Trader role. Use keywords from the job description to show that you understand what we're looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it's relevant to the role. Make it easy for us to see why you're a great fit!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Axon Labs
✨Know Your Models Inside Out
Make sure you can explain your predictive models and alpha signals clearly. Be ready to discuss the statistical, ML, and DL approaches you've used, and how they apply to streaming time-series data. This shows you not only understand the theory but can also apply it practically.
✨Demonstrate Your Trading Strategy Experience
Prepare to talk about your experience owning the full lifecycle of a trading strategy. Highlight specific examples from idea generation to live execution, and be ready to discuss challenges you faced and how you overcame them. This will show your depth of knowledge in market microstructure and order-book dynamics.
✨Show Off Your Coding Skills
Since strong Python and C++ skills are crucial for this role, be prepared to discuss your coding experience. You might even want to bring along some code samples or projects that demonstrate your ability to write clean, reliable, performance-oriented code. This will give you an edge in proving your technical capabilities.
✨Collaborate and Communicate
As collaboration is key in this role, think of examples where you've worked with others on real-time risk monitoring or control infrastructure. Be ready to discuss how you communicate complex ideas to non-technical team members, as this will highlight your teamwork and communication skills.
