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- Tasks: Develop advanced forecasting models and analyse market data for trading strategies.
- Company: Leading prop-trading firm in Greater London with a focus on innovation.
- Benefits: Flexible remote work, autonomy, and a supportive environment for creativity.
- Why this job: Shape trading strategies using cutting-edge machine learning techniques.
- Qualifications: 7+ years in quantitative research, strong statistical analysis, and Python proficiency.
- Other info: Great opportunity for career growth in a dynamic trading environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading prop-trading firm in Greater London is seeking a Senior Quantitative Researcher with expertise in machine learning for time series. You will be responsible for developing advanced forecasting models and analyzing market data to shape trading strategies.
The ideal candidate has over 7 years of experience in quantitative research, a strong background in statistical analysis, and proficiency in tools like Python and PyTorch.
This role offers flexibility, autonomy, and a supportive environment for innovation.
Senior Time-Series ML Researcher — Remote Trading employer: Redbridge
Contact Detail:
Redbridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Time-Series ML Researcher — Remote Trading
✨Tip Number 1
Network like a pro! Reach out to folks in the trading and machine learning space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your forecasting models and analyses. 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 statistical analysis and Python skills, and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who take the initiative. Plus, it helps us keep track of your application better.
We think you need these skills to ace Senior Time-Series ML Researcher — Remote Trading
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in quantitative research and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in Python and PyTorch!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about time-series analysis and how your background makes you a perfect fit for our team. We love seeing genuine enthusiasm!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We’re keen to see examples of your forecasting models and any innovative strategies you've developed.
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. Plus, it’s super easy!
How to prepare for a job interview at Redbridge
✨Know Your Models Inside Out
Make sure you can discuss your experience with forecasting models in detail. Be prepared to explain the algorithms you've used, why you chose them, and how they performed in real-world scenarios. This shows your depth of knowledge and practical application.
✨Brush Up on Statistical Analysis
Since the role requires a strong background in statistical analysis, review key concepts and be ready to tackle questions that test your understanding. You might even want to prepare a few examples of how you've applied these techniques in your previous work.
✨Demonstrate Your Coding Skills
Proficiency in Python and PyTorch is crucial for this position. Consider preparing a small coding challenge or discussing a project where you implemented machine learning models. This will help showcase your technical skills and problem-solving abilities.
✨Show Enthusiasm for Innovation
This firm values a supportive environment for innovation, so express your passion for exploring new ideas and technologies. Share any personal projects or research that demonstrate your proactive approach to learning and development in the field of quantitative research.
