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- Tasks: Build predictive trading models and enhance trading efficiency with innovative teams.
- Company: Leading algorithmic trading firm in London with a collaborative culture.
- Benefits: Unique opportunity in a dynamic trading environment with career growth.
- Why this job: Engage in cutting-edge trading technology and make a real impact.
- Qualifications: Studying a quantitative discipline with programming skills in Python or C++.
- Other info: Perfect for 2026 graduates looking to kickstart their careers.
The predicted salary is between 36000 - 60000 £ per year.
A leading algorithmic trading firm in London is seeking an Algorithm Developer for 2026 graduates. The role involves building predictive trading models and working closely with teams to enhance trading efficiency.
Candidates should be studying in a quantitative discipline and possess programming skills in Python or C++.
This position offers a unique opportunity to engage in a dynamic trading environment within a collaborative culture.
Quant Algorithm Developer for Trading Models (2026 Grads) in City of London employer: Hudson River Trading
Contact Detail:
Hudson River Trading Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Algorithm Developer for Trading Models (2026 Grads) in City of London
✨Tip Number 1
Network like a pro! Reach out to alumni or professionals in the algorithmic trading space. A friendly chat can lead to valuable insights and even job referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models or any relevant projects. This is your chance to demonstrate your programming prowess in Python or C++.
✨Tip Number 3
Prepare for technical interviews by brushing up on algorithms and data structures. Practice coding challenges online to get comfortable with problem-solving under pressure.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for fresh talent, and applying directly can give you an edge in the hiring process.
We think you need these skills to ace Quant Algorithm Developer for Trading Models (2026 Grads) in City of London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python or C++. We want to see how you can apply these skills to build predictive trading models, so don’t hold back!
Quantitative Discipline Matters: Since we’re looking for candidates studying in a quantitative discipline, be sure to mention your degree and any relevant coursework. This helps us understand your background and how it fits with the role.
Collaborative Spirit: We love teamwork! In your application, share examples of how you've worked collaboratively in the past. It’ll show us that you’re ready to jump into our dynamic trading environment.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at Hudson River Trading
✨Know Your Algorithms
Brush up on your knowledge of predictive trading models and algorithms. Be prepared to discuss specific algorithms you've worked with, how they function, and their applications in trading. This shows your passion and understanding of the field.
✨Showcase Your Coding Skills
Since programming in Python or C++ is crucial for this role, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to boost your confidence.
✨Understand the Trading Environment
Familiarise yourself with the current trends in algorithmic trading and the specific firm’s approach. Being able to discuss recent developments or news in the trading world can set you apart and show your genuine interest in the industry.
✨Emphasise Team Collaboration
This role involves working closely with teams, so highlight any experiences where you've successfully collaborated on projects. Share examples that demonstrate your ability to communicate effectively and work well within a team setting.
