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- Tasks: Join a team applying machine learning to analyse large datasets for predictive modelling.
- Company: A pioneering hedge fund focused on quantitative research and collaboration.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and learning.
- Why this job: Be part of an innovative team that values academic principles and real-world applications.
- Qualifications: PhD in Mathematical Machine Learning from a top university; finance experience is a plus.
- Other info: Ideal for candidates with 0-2 years of experience looking to enter quantitative trading.
The predicted salary is between 36000 - 60000 £ per year.
A pioneering and quantitatively driven hedge fund is hiring a Junior Quantitative Researcher for their Mid-Frequency Equity Statistical Arbitrage team. As part of their expansion, they are applying sophisticated machine learning techniques to analyze a variety of large datasets to enhance predictive models. The business values collaboration and takes an academic approach to research. Anyone joining the business will share similar principles.
The right candidate will have a stellar academic background, having studied Mathematical Machine Learning at PhD level from a top university. While finance experience is preferred, it is not a prerequisite if machine learning techniques (such as deep learning) have been applied to other real-world applications. Experience between 0-2 years is ideal.
If you fit the criteria and are looking to get into quantitative trading, we would love to hear from you.
Quantitative Researcher, Machine Learning (Equities) employer: AI Search
Contact Detail:
AI Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher, Machine Learning (Equities)
✨Tip Number 1
Network with professionals in the quantitative finance and machine learning fields. Attend industry conferences, webinars, or local meetups to connect with people who work in hedge funds or similar environments. This can help you gain insights into the company culture and potentially get a referral.
✨Tip Number 2
Familiarise yourself with the latest machine learning techniques and their applications in finance. Consider working on personal projects or contributing to open-source projects that showcase your skills in deep learning and statistical analysis, as this will demonstrate your practical experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of quantitative methods and algorithms. Practice coding challenges related to data analysis and machine learning, as well as discussing your past projects and how they relate to the role you're applying for.
✨Tip Number 4
Showcase your passion for quantitative research and machine learning in your conversations with recruiters or during networking events. Discuss recent advancements in the field and how they could apply to the role, demonstrating your enthusiasm and commitment to continuous learning.
We think you need these skills to ace Quantitative Researcher, Machine Learning (Equities)
Some tips for your application 🫡
Highlight Your Academic Background: Make sure to emphasise your stellar academic achievements, particularly if you have studied Mathematical Machine Learning at PhD level. Mention any relevant coursework or projects that showcase your expertise in machine learning techniques.
Showcase Relevant Experience: Even if you don't have direct finance experience, highlight any practical applications of machine learning techniques, such as deep learning, in real-world scenarios. Include internships, research projects, or personal projects that demonstrate your skills.
Demonstrate Collaboration Skills: Since the company values collaboration, include examples of teamwork in your application. Discuss any group projects or collaborative research experiences that illustrate your ability to work well with others.
Tailor Your Application: Customise your CV and cover letter to align with the company's focus on quantitative research and machine learning. Use specific language from the job description to show that you understand their needs and how you can contribute.
How to prepare for a job interview at AI Search
✨Showcase Your Academic Background
Be prepared to discuss your PhD research in Mathematical Machine Learning. Highlight any specific projects or findings that demonstrate your expertise and how they relate to the role.
✨Demonstrate Machine Learning Applications
Even if you lack direct finance experience, be ready to explain how you've applied machine learning techniques, like deep learning, in real-world scenarios. Use concrete examples to illustrate your problem-solving skills.
✨Emphasise Collaboration Skills
Since the company values collaboration, share experiences where you've worked effectively in a team. Discuss how you contributed to group projects and how you handle differing opinions.
✨Prepare for Technical Questions
Expect technical questions related to machine learning algorithms and statistical methods. Brush up on key concepts and be ready to solve problems on the spot, demonstrating your analytical thinking.
