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- Tasks: Apply deep learning methods to complex research projects in quantitative finance.
- Company: Leading quantitative research firm based in Greater London.
- Benefits: Competitive salary package and comprehensive benefits.
- Why this job: Join a creative team and make an impact in the finance sector.
- Qualifications: PhD or Master's in Computer Science/Mathematics with 5+ years experience.
- Other info: Collaborative environment focused on continuous project improvement.
The predicted salary is between 48000 - 72000 £ per year.
A leading quantitative research firm in Greater London is looking for a research scientist to apply deep learning methods to complex research projects. This role requires a PhD or Master's degree in Computer Science or Mathematics, and at least 5 years of relevant experience. Successful candidates will be creative thinkers with strong communication skills and a solid background in mathematics. The role includes continuous project improvement and teamwork. A competitive salary package and comprehensive benefits are offered.
Senior Deep Learning Scientist - Quantitative Finance employer: P2P
Contact Detail:
P2P Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Deep Learning Scientist - Quantitative Finance
✨Tip Number 1
Network like a pro! Reach out to professionals in the quantitative finance space on LinkedIn or at industry events. We can’t stress enough how valuable personal connections can be in landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your deep learning projects and any relevant research. This is your chance to demonstrate your creativity and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex concepts in simple terms, as teamwork and clear communication are key in this role. We want you to stand out!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Deep Learning Scientist - Quantitative Finance
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your deep learning expertise and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Senior Deep Learning Scientist position. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Creative: This role is all about creative thinking, so let your personality shine through in your application. Share unique insights or approaches you’ve taken in past projects that demonstrate your innovative mindset.
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!
How to prepare for a job interview at P2P
✨Brush Up on Your Deep Learning Knowledge
Make sure you're well-versed in the latest deep learning techniques and frameworks. Review your past projects and be ready to discuss how you've applied these methods in quantitative finance. This will show your expertise and passion for the field.
✨Prepare for Technical Questions
Expect to face technical questions that assess your mathematical skills and programming knowledge. Practice explaining complex concepts clearly, as strong communication is key. Use examples from your experience to demonstrate your problem-solving abilities.
✨Showcase Your Creativity
Think of innovative ways you've approached research problems in the past. Be prepared to discuss how you can bring fresh ideas to the team and contribute to continuous project improvement. Highlight any unique methodologies you've developed.
✨Emphasise Teamwork and Collaboration
Since this role involves teamwork, be ready to share experiences where you've successfully collaborated with others. Discuss how you handle feedback and contribute to a positive team environment, as this will resonate well with the interviewers.
