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- Tasks: Join a dynamic quant team to analyse financial datasets and develop trading models.
- Company: A leading tier-1 hedge fund in London with a collaborative culture.
- Benefits: Gain exposure to advanced quantitative techniques and innovative research opportunities.
- Why this job: Contribute to impactful projects while working alongside top-tier academics in finance.
- Qualifications: PhD in a quantitative field and strong programming skills in Python required.
- Other info: Ideal for PhD and Post-Doc graduates starting in 2025/early 2026.
The predicted salary is between 28800 - 48000 £ per year.
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
- 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.
- Experience with data analysis tools.
- Experience with machine learning techniques and tools.
- Knowledge of global macroeconomic factors and their impact on financial markets.
Graduate Quantitative Analyst employer: Selby Jennings
Contact Detail:
Selby Jennings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Quantitative Analyst
✨Tip Number 1
Network with professionals in the finance and quantitative analysis sectors. Attend industry conferences, seminars, or webinars where you can meet people from hedge funds and learn about their work culture. This can help you gain insights into what they value in candidates.
✨Tip Number 2
Engage in relevant online communities and forums focused on quantitative finance and machine learning. Participating in discussions or sharing your own insights can help you establish your expertise and make connections that could lead to job opportunities.
✨Tip Number 3
Consider working on personal projects or contributing to open-source projects that showcase your programming skills in Python and your understanding of quantitative techniques. This practical experience can be a great talking point during interviews.
✨Tip Number 4
Stay updated on the latest trends in quantitative finance and machine learning by reading research papers, articles, and books. Being knowledgeable about current developments will not only enhance your skills but also impress potential employers during interviews.
We think you need these skills to ace Graduate Quantitative Analyst
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 data analysis tools.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for quantitative analysis and finance. Mention specific projects or research that align with the responsibilities of the role, particularly in machine learning and quantitative trading.
Highlight Relevant Experience: In your application, include any internships, research projects, or work experiences that demonstrate your analytical skills and familiarity with financial datasets. Be specific about your contributions and outcomes.
Showcase Collaborative Skills: Since the team values collaboration, mention any experiences where you worked effectively in a team setting. Highlight how you contributed to group projects or research initiatives, showcasing your ability to innovate and support others.
How to prepare for a job interview at Selby Jennings
✨Showcase Your Academic Achievements
Make sure to highlight your PhD or Post-Doc research during the interview. Discuss specific projects, methodologies, and outcomes that demonstrate your expertise in quantitative fields like Mathematics or Machine Learning.
✨Demonstrate Programming Proficiency
Since strong programming skills in Python are essential, be prepared to discuss your experience with coding. You might even be asked to solve a problem on the spot, so brush up on your Python skills and be ready to showcase your coding abilities.
✨Prepare for Technical Questions
Expect questions related to quantitative analysis, machine learning techniques, and financial datasets. Review key concepts and be ready to explain how you would approach analysing data or developing trading models.
✨Emphasise Team Collaboration
The role requires working as part of a collaborative team. Be ready to share examples of how you've successfully worked in teams before, highlighting your ability to contribute innovative ideas and support your colleagues in achieving common goals.
