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- Tasks: Lead the development of fundamental equity strategies and manage a dedicated pod.
- Company: Join a boutique asset manager in London known for its innovative approach.
- Benefits: Enjoy a dynamic work environment with opportunities for professional growth.
- Why this job: This role offers a chance to elevate your career in a collaborative, high-impact setting.
- Qualifications: 6+ years in alpha generation as a quant researcher or trader; strong STEM and machine learning skills required.
- Other info: Ideal for those looking to transition from research or trading into a leadership role.
The predicted salary is between 48000 - 84000 £ per year.
GCS Quant has partnered with a boutique asset manager in London on the look out for Portfolio Managers armed with Fundamental Equity Strategies.
Due to their structure, this client would accept Quant Researchers and Traders with a 4+ year track to come in to set up those strategies as a pod.
Below is listed some key requirements:
- 6+ years of experience working within an front office alpha gen environment as a quant researcher or trader.
- Ideally looking for experience developing macro strategies for US Equities (fundamental).
- 3+ years of signal track and a strong risk allocation.
- Exceptional STEM skills (probability, stats, computer science).
- Exceptional Machine Learning fundamentals to derive insights.
Please apply if you are a QR or Quant Trader looking for a step up.
Portfolio Manager employer: GCS Quant
Contact Detail:
GCS Quant Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Portfolio Manager
✨Tip Number 1
Make sure to highlight your experience in developing macro strategies for US Equities during networking events or conversations. This will help you stand out as a candidate who understands the specific needs of the role.
✨Tip Number 2
Connect with professionals in the asset management industry on platforms like LinkedIn. Engaging with them can provide insights into the company culture and potentially lead to referrals.
✨Tip Number 3
Stay updated on the latest trends in machine learning and quantitative finance. Being able to discuss recent developments can demonstrate your passion and expertise during interviews.
✨Tip Number 4
Consider joining relevant online forums or groups where quant researchers and traders share insights. This can help you build connections and learn about job openings before they are widely advertised.
We think you need these skills to ace Portfolio Manager
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 6+ years of experience in a front office alpha generation environment. Detail your roles as a quant researcher or trader, and specifically mention any experience you have developing macro strategies for US Equities.
Showcase Your Skills: Clearly outline your exceptional STEM skills, particularly in probability, statistics, and computer science. Include specific examples of how you've applied these skills in your previous roles.
Demonstrate Machine Learning Knowledge: Since the role requires strong fundamentals in machine learning, provide examples of projects or tasks where you've utilized machine learning techniques to derive insights. This will help you stand out as a candidate.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Use keywords from the listing, such as 'quant researcher', 'trader', 'risk allocation', and 'signal track' to ensure your application resonates with the hiring team.
How to prepare for a job interview at GCS Quant
✨Showcase Your Experience
Make sure to highlight your 6+ years of experience in a front office alpha generation environment. Be prepared to discuss specific projects or strategies you've worked on, especially those related to macro strategies for US Equities.
✨Demonstrate Your Quant Skills
Since exceptional STEM skills are crucial, be ready to discuss your knowledge in probability, statistics, and computer science. Prepare examples of how you've applied these skills in real-world scenarios.
✨Discuss Machine Learning Applications
Given the importance of machine learning fundamentals, come prepared to explain how you've used machine learning techniques to derive insights in your previous roles. Share specific examples that showcase your analytical capabilities.
✨Prepare for Technical Questions
Expect technical questions related to signal tracking and risk allocation. Brush up on relevant concepts and be ready to solve problems on the spot, demonstrating your quantitative reasoning and problem-solving skills.
