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- Tasks: Develop advanced ML models for forecasting complex time series in a dynamic environment.
- Company: Leading prop-trading firm in London with a focus on innovation.
- Benefits: Flexible remote work, competitive salary, and opportunities for professional growth.
- Why this job: Shape research and trading strategies while working with cutting-edge technology.
- Qualifications: 7+ years in quantitative research or systematic trading, strong Python skills.
- Other info: Autonomous role that encourages innovative thinking and collaboration.
The predicted salary is between 43200 - 72000 £ per year.
A prop-trading firm in London seeks an experienced professional to develop advanced ML models for forecasting complex time series. The ideal candidate will have over 7 years in quantitative research or systematic trading, a strong background in Python, and the ability to communicate complex ideas clearly. This role offers a flexible work environment focused on innovation and autonomy, allowing you to truly shape research and trading strategies.
Senior Time-Series ML Researcher - Remote employer: Redbridge
Contact Detail:
Redbridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Time-Series ML Researcher - Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the prop-trading and ML 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 best time-series ML projects. This is your chance to demonstrate your expertise beyond the written application.
✨Tip Number 3
Prepare for those interviews! Brush up on your Python skills and be ready to discuss your past experiences in quantitative research. Practice explaining complex ideas simply.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. It shows you're genuinely interested in joining our innovative team.
We think you need these skills to ace Senior Time-Series ML Researcher - Remote
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 7+ years in quantitative research or systematic trading. We want to see how your background aligns with the role, so don’t hold back on those impressive projects you've worked on!
Python Proficiency is Key: Since a strong background in Python is essential, include specific examples of how you've used it in your previous roles. We love seeing practical applications of your skills, so share any relevant ML models you've developed.
Communicate Clearly: This role requires the ability to communicate complex ideas clearly. Use your application to demonstrate this skill by keeping your language straightforward and avoiding jargon where possible. We appreciate clarity just as much as complexity!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Redbridge
✨Know Your Time-Series Inside Out
Make sure you brush up on your time-series analysis skills. Be prepared to discuss different forecasting techniques and how you've applied them in past projects. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Python Proficiency
Since Python is a key requirement, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot or discuss your previous projects. Have examples ready that highlight your ability to develop advanced ML models using Python.
✨Communicate Clearly and Confidently
This role requires clear communication of complex ideas. Practice explaining your research and findings in simple terms. Think about how you would present your work to someone without a technical background, as this will be crucial in the interview.
✨Embrace the Flexibility and Innovation
The firm values innovation and autonomy, so be prepared to discuss how you approach research and trading strategies. Share examples of how you've taken initiative in past roles and how you plan to contribute to their innovative environment.
