At a Glance
- Tasks: Develop machine learning models for trading strategies and create high-quality signals.
- Company: Join a top-tier global investment manager with a collaborative culture and rapid growth.
- Benefits: Enjoy competitive compensation based on performance and flexible work arrangements.
- Other info: No up-to-date CV needed; just bring your passion and skills!
- Why this job: Be part of a dynamic team at a leading firm making waves in the finance world.
- Qualifications: Experience in financial services, strong machine learning background, and proficiency in Python/R required.
The predicted salary is between 43200 - 72000 £ per year.
Looking for a deep learning role that could make the Mariana trench seem like a puddle? This global investment manager hires asset class experts, such as an ex-portfolio manager from a Tier 1 hedge fund to grow and manage risk. You’re going to be part of headcount growth this year to over 1000 which includes a 20% increase into research.
You’ll collaborate to develop different machine learning models for trading strategies and create high quality signals. You'll be working at an MFT systematic multi-strat fund whose performance has been top tier over the last few years, with AUM and headcount growing. Despite their larger size, their structure remains collaborative and not solely pod-shop based, a rare find for an investment firm of this calibre.
You will ideally have prior experience in a fund within financial services with a strong background in machine learning or a related field. Proficiency in Python/R and experience with deep learning frameworks such as PyTorch or TensorFlow will also be required.
Want to join? Get in touch. Salary and total compensation is purely based on performance of your models and the overall business – we can discuss your comp requirements in depth when you get in touch. No up-to-date CV required.
Quantitative Researcher at one of the most well-paid multi-strat Quant firms employer: LinkedIn
Join a leading global investment manager renowned for its collaborative work culture and commitment to employee growth. As a Quantitative Researcher, you'll have the opportunity to develop cutting-edge machine learning models in a top-tier systematic multi-strat fund, all while enjoying competitive compensation based on your performance. With a focus on innovation and a supportive environment, this firm is an excellent employer for those looking to make a significant impact in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher at one of the most well-paid multi-strat Quant firms
✨Tip Number 1
Network with professionals in the quantitative finance space. Attend industry conferences, webinars, or local meetups to connect with people who work at similar firms. This can help you gain insights into the company culture and potentially get a referral.
✨Tip Number 2
Showcase your machine learning projects on platforms like GitHub. Having a portfolio of your work can demonstrate your skills in Python/R and deep learning frameworks, making you stand out to recruiters looking for practical experience.
✨Tip Number 3
Stay updated on the latest trends in quantitative research and machine learning. Follow relevant blogs, podcasts, and publications to discuss these topics during interviews, showing your passion and knowledge in the field.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm questions related to machine learning. Familiarise yourself with common problems and solutions that are relevant to trading strategies to impress your interviewers.
We think you need these skills to ace Quantitative Researcher at one of the most well-paid multi-strat Quant firms
Some tips for your application 🫡
Tailor Your CV:Even though an up-to-date CV isn't required, it's still a good idea to tailor your CV to highlight your experience in financial services and machine learning. Focus on relevant projects and skills that align with the role.
Highlight Technical Skills:Make sure to emphasise your proficiency in Python/R and any experience you have with deep learning frameworks like PyTorch or TensorFlow. Provide specific examples of how you've used these tools in previous roles.
Showcase Collaboration Experience:Since the firm values collaboration, include examples of how you've worked effectively in teams. Mention any cross-functional projects or collaborative research efforts that demonstrate your ability to work well with others.
Express Your Passion for Deep Learning:In your application, convey your enthusiasm for deep learning and quantitative research. Discuss any personal projects or ongoing learning in this area to show your commitment and interest in the field.
How to prepare for a job interview at LinkedIn
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, R, and deep learning frameworks like PyTorch or TensorFlow. Bring examples of projects you've worked on that demonstrate your proficiency in these areas.
✨Understand the Firm's Strategy
Research the firm's investment strategies and recent performance. Being able to articulate how your skills can contribute to their multi-strat approach will show your genuine interest and alignment with their goals.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving abilities in quantitative research. Practice explaining your thought process clearly and concisely, as this is crucial in a collaborative environment.
✨Demonstrate Collaborative Spirit
Since the firm values collaboration, be ready to discuss past experiences where you worked effectively in a team. Highlight how you contributed to group projects and how you handle differing opinions.
