Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a collaborative team to enhance investment strategies and develop innovative quantitative models.
- Company: Dynamic financial firm focused on delivering top-notch investment outcomes.
- Benefits: Flexible working hours, hybrid options, and opportunities for professional growth.
- Why this job: Make a real impact in finance while honing your quantitative skills.
- Qualifications: Strong financial knowledge, Python proficiency, and experience with quantitative analysis.
- Other info: Exciting career prospects in a supportive and innovative environment.
The predicted salary is between 36000 - 60000 £ per year.
Our people work differently depending on their jobs and needs. From hybrid working to flexible hours, we have plenty of options that help our people to thrive. This role is based in the United Kingdom and as such all normal working days must be carried out in the United Kingdom.
Responsibilities
- Become part of a highly collaborative team, playing a key role in delivering best-in-class investment outcomes for our clients.
- Your work will be vital in helping us develop potential investable products, which will benefit our ultra-high net worth clients.
- You’ll have the chance to conduct independent research into new potential quantitative models, building on your existing skill sets.
What you’ll do
- As a Quantitative Analyst within the Asset Allocation Team, you’ll use your financial and quantitative expertise to maintain existing and build new models to continually enhance our investment decision-making capabilities.
- Producing research and trading ideas for tactical asset allocation and researching other ways of enhancing portfolio returns.
- Enhancing expected returns forecasts, suggesting or modifying assets for inclusion and backtesting and calculating risk contributions of changes to the current strategic asset allocation.
- Developing and maintaining quantitative tools that support portfolio construction and investment decision-making.
The skills you’ll need
- We’re looking for someone with strong financial and macroeconomic knowledge, ideally with experience in multi-asset research and/or portfolio construction.
- Proficiency in Python for data analysis and quantitative modelling is also essential.
- Experience or working knowledge of capital market assumption modelling.
- Practical experience with quantitative Python libraries (e.g. pandas, NumPy, statsmodels, SciPy and scikit-learn).
- A solid understanding of private banking across wealth segments with awareness of relevant regulatory frameworks.
Quantitative Analyst employer: Coutts
Contact Detail:
Coutts Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and quantitative analysis space. Use platforms like LinkedIn to connect with people who work at companies you're interested in. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative models and analyses. This could be through GitHub or a personal website. When you apply, share this with potential employers to demonstrate your expertise in Python and data analysis.
✨Tip Number 3
Prepare for interviews by brushing up on your financial knowledge and quantitative skills. Be ready to discuss your past projects and how they relate to the role. Practising common interview questions can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight how your skills align with the responsibilities of a Quantitative Analyst, and let your passion for the role shine through.
We think you need these skills to ace Quantitative Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Analyst role. Highlight your financial and macroeconomic knowledge, and don’t forget to showcase your Python skills and experience with quantitative modelling. We want to see how your background aligns with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your skills can contribute to our team. Be specific about your experience in multi-asset research and portfolio construction – we love details!
Showcase Your Research Skills: As a Quantitative Analyst, independent research is key. In your application, mention any relevant projects or models you've worked on. This will demonstrate your ability to conduct research and develop investable products, which is crucial for us.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Coutts
✨Know Your Numbers
As a Quantitative Analyst, you'll need to demonstrate your financial and macroeconomic knowledge. Brush up on key concepts related to multi-asset research and portfolio construction. Be ready to discuss how you've applied these in past roles or projects.
✨Showcase Your Python Skills
Proficiency in Python is essential for this role. Prepare to talk about your experience with data analysis and quantitative modelling using Python libraries like pandas and NumPy. Consider bringing examples of your work or even a small project that highlights your skills.
✨Research the Company’s Investment Strategies
Familiarise yourself with the company’s approach to investment and asset allocation. Understanding their current models and strategies will help you tailor your responses and show that you're genuinely interested in contributing to their goals.
✨Prepare for Technical Questions
Expect technical questions that assess your quantitative skills and problem-solving abilities. Practice explaining complex concepts clearly and concisely, as you may need to backtest models or discuss risk contributions during the interview.
