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- Tasks: Build and maintain predictive trading models using statistical analysis on market data.
- Company: Leading algorithmic trading firm in Greater London with a dynamic environment.
- Benefits: Gain hands-on experience in algorithmic trading and enhance your programming skills.
- Why this job: Dive into the exciting world of trading and make a real impact with your skills.
- Qualifications: Pursuing quantitative disciplines with programming experience in Python or C++.
- Other info: Collaborate with a talented team and explore excellent career growth opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A leading algorithmic trading firm in Greater London is seeking Algorithm Developers to build and maintain predictive trading models. The role involves using statistical analysis on extensive market data and working closely with a team to improve trading efficiency.
Ideal candidates are students pursuing quantitative disciplines with programming experience in Python or C++.
This opportunity promises a dynamic environment in the exciting world of algorithmic trading.
Quant Researcher & Algo Developer - Trading Models (London) employer: Hudson River Trading
Contact Detail:
Hudson River Trading Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher & Algo Developer - Trading Models (London)
✨Tip Number 1
Network like a pro! Reach out to professionals in the algorithmic trading space on LinkedIn. A friendly message can go a long way, and you never know who might have a lead on an opportunity.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python or C++. This is your chance to demonstrate your programming prowess and how you can contribute to predictive trading models.
✨Tip Number 3
Prepare for technical interviews! Brush up on your statistical analysis and coding skills. Practice common algorithm questions and be ready to discuss your thought process during problem-solving.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Don’t miss out on the chance to join a dynamic team in the exciting world of algorithmic trading.
We think you need these skills to ace Quant Researcher & Algo Developer - Trading Models (London)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming experience in Python or C++. We want to see how you can apply your skills to build and maintain predictive trading models.
Quantitative Focus is Key: Since we’re looking for candidates from quantitative disciplines, don’t forget to mention any relevant coursework or projects. This will help us understand your background in statistical analysis.
Team Player Vibes: We value collaboration, so if you've worked in teams before, share those experiences! Let us know how you’ve contributed to improving efficiency in past projects.
Apply Through Our Website: To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Hudson River Trading
✨Know Your Algorithms
Brush up on your knowledge of algorithmic trading and predictive models. Be prepared to discuss specific algorithms you've worked with, how they function, and their impact on trading efficiency. 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 abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to boost your confidence.
✨Understand Statistical Analysis
Familiarise yourself with statistical methods relevant to trading models. Be prepared to explain how you’ve applied these techniques in past projects or coursework. This will highlight your analytical skills and suitability for the role.
✨Teamwork Makes the Dream Work
This role involves working closely with a team, so be ready to discuss your experience collaborating with others. Share examples of how you contributed to team projects and how you handle feedback, as this will demonstrate your ability to thrive in a dynamic environment.
