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- Tasks: Join a dynamic quant team to analyse financial datasets and develop innovative trading models.
- Company: A leading tier-1 hedge fund in London with a collaborative and high-achieving culture.
- Benefits: Full-time role with opportunities for growth and development in a prestigious environment.
- Why this job: Contribute to cutting-edge research and make an impact in the finance world with your ideas.
- Qualifications: PhD in a quantitative field and strong programming skills in Python required.
- Other info: Ideal for recent graduates looking to start their career in finance and quantitative research.
The predicted salary is between 28800 - 48000 £ per year.
Quantitative Researcher │PhD and Post-Doc
Quantitative Researcher │PhD and Post-Doc
We are seeking talented PhD and Post-Doc. graduates to join a successful centralised quant team at a tier-1 hedge fund in London. The team is highly collaborative, made up of people from incredibly strong academic backgrounds and they are now looking to onboard PhD and Post-Doc. graduates, starting in 2025/early 2026. The ideal candidate will have a PhD in a quantitative field such as Mathematics, Statistics, Computer Science, Machine Learning or Physics.
You will be developing skills in advanced quantitative techniques across a range of data types, markets and asset classes, in order to enhance their existing strategies and drive implementation of new signals and models. They have had several very successful years and as part of their team scale out they are looking for PhD and Post-Doc. graduates to contribute innovative ideas, aid with research, design and implementation.
Key Responsibilities:
- Analysing and evaluating financial and alternative datasets
- Researching existing and developing new techniques in machine learning
- Researching, developing and implementing quantitative trading signals/models
- Developing and maintaining modelling infrastructure
- Supporting production trading operations
Qualifications:
- Have a PhD in a quantitative field such as Mathematics, Statistics, Computer Science, Machine Learning or Physics.
- Strong programming skills in Python.
- Excellent problem-solving skills and attention to detail.
- Strong analytical and mathematical background.
- Ability to work independently and as part of a team.
Preferred Qualifications:
- Experience with data analysis tools.
- Experience with machine learning techniques and tools.
- Knowledge of global macroeconomic factors and their impact on financial markets.
Seniority level
-
Seniority level
Entry level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Finance
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Quantitative Researcher │PhD and Post-Doc employer: Selby Jennings
Contact Detail:
Selby Jennings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher │PhD and Post-Doc
✨Tip Number 1
Network with professionals in the finance and quantitative research fields. Attend industry conferences, seminars, or webinars where you can meet potential colleagues and mentors. Engaging with experts can provide insights into the role and may even lead to referrals.
✨Tip Number 2
Showcase your programming skills, particularly in Python, through personal projects or contributions to open-source initiatives. This not only demonstrates your technical abilities but also your passion for quantitative research, making you a more attractive candidate.
✨Tip Number 3
Stay updated on the latest trends in machine learning and quantitative finance. Follow relevant blogs, podcasts, and research papers to deepen your understanding and be prepared to discuss these topics during interviews.
✨Tip Number 4
Prepare to discuss your research experience in detail. Be ready to explain your methodologies, findings, and how they can apply to real-world financial problems. This will demonstrate your analytical skills and ability to contribute to the team.
We think you need these skills to ace Quantitative Researcher │PhD and Post-Doc
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD or Post-Doc qualifications in a quantitative field. Emphasise relevant skills such as programming in Python, problem-solving abilities, and any experience with machine learning techniques.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your academic background and research align with the responsibilities of the Quantitative Researcher position, particularly in developing and implementing quantitative trading models.
Showcase Relevant Projects: Include specific examples of projects or research you have conducted that demonstrate your analytical skills and familiarity with financial datasets. Highlight any innovative ideas you contributed that could be relevant to the hedge fund's strategies.
Proofread and Edit: Before submitting your application, thoroughly proofread your documents. Ensure there are no grammatical errors or typos, as attention to detail is crucial in this field. A polished application reflects your professionalism and commitment.
How to prepare for a job interview at Selby Jennings
✨Showcase Your Technical Skills
Make sure to highlight your programming skills, especially in Python, during the interview. Be prepared to discuss specific projects or experiences where you applied advanced quantitative techniques or machine learning methods.
✨Demonstrate Problem-Solving Abilities
Expect to face technical questions that assess your analytical and problem-solving skills. Practice explaining your thought process clearly and logically, as this will showcase your ability to tackle complex challenges.
✨Research the Company and Team
Familiarise yourself with the hedge fund's recent successes and strategies. Understanding their approach to quantitative research will allow you to ask insightful questions and demonstrate your genuine interest in joining their team.
✨Prepare for Collaborative Scenarios
Since the role involves working in a highly collaborative environment, be ready to discuss your experiences working in teams. Highlight how you contributed to group projects and how you handle differing opinions or challenges within a team setting.