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- Tasks: Design models and build trading infrastructure for prediction markets.
- Company: Leading financial trading firm with a dynamic startup-like environment.
- Benefits: Competitive salary, flexible work locations, and opportunities for growth.
- Why this job: Join a cutting-edge team and make an impact in financial forecasting.
- Qualifications: Relevant degree and strong Python engineering skills required.
- Other info: Self-motivated individuals with clear communication thrive here.
The predicted salary is between 36000 - 60000 £ per year.
A leading financial trading firm is hiring a Prediction Market Quant Engineer to design models and build trading infrastructure for prediction markets. The successful candidate will develop probabilistic models, manage risk, and ensure system reliability.
Applicants should possess a relevant degree and strong Python engineering skills. This role offers a dynamic startup-like environment and requires a self-motivated individual with clear communication abilities.
The position is based in locations including London, Zurich, New York, or Hong Kong.
Prediction Markets Quant Engineer: Real-Time Forecasts in London employer: G-20 Group
Contact Detail:
G-20 Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Prediction Markets Quant Engineer: Real-Time Forecasts in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and probabilistic models. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your thought process. Practising common questions can help you feel more confident.
✨Tip Number 4
Apply through our website! We love seeing applications directly from candidates who are excited about joining us. It shows initiative and helps us get to know you better.
We think you need these skills to ace Prediction Markets Quant Engineer: Real-Time Forecasts in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python engineering skills and any relevant experience in your application. We want to see how you can bring your technical expertise to the table!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Prediction Market Quant Engineer role. We love seeing candidates who take the time to align their experiences with what we’re looking for.
Communicate Clearly: Since clear communication is key in this role, ensure your application is well-structured and easy to read. We appreciate candidates who can convey their thoughts effectively, so don’t hold back!
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 G-20 Group
✨Know Your Models
Make sure you brush up on your probabilistic models before the interview. Be ready to discuss how you've applied these in real-world scenarios, especially in trading contexts. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Python Skills
Since strong Python engineering skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common algorithms and data structures. Familiarise yourself with libraries relevant to quantitative finance as well.
✨Communicate Clearly
In a dynamic environment like this, clear communication is key. Practice explaining complex concepts in simple terms. You may need to collaborate with non-technical team members, so being able to articulate your ideas clearly will set you apart.
✨Understand Risk Management
Risk management is crucial in trading. Be prepared to discuss your approach to managing risk in your previous projects. Think of examples where you identified potential risks and how you mitigated them, as this will demonstrate your proactive mindset.
