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- Tasks: Build quantitative models and analyse data to support investment decisions.
- Company: Leading investment firm in London with a focus on innovation.
- Benefits: Competitive salary up to £100,000, bonus, and hybrid work model.
- Why this job: Join a dynamic team and make impactful investment decisions using your analytical skills.
- Qualifications: Master's or PhD in a quantitative field and proficiency in Python.
- Other info: Exciting opportunity for career growth in a fast-paced environment.
The predicted salary is between 60000 - 84000 £ per year.
An investment firm in London is seeking a Quantitative Analyst/Data Scientist to enhance their Credit & Asset-Backed Finance team. The role involves building quantitative models and conducting in-depth data analysis to support investment decisions.
Ideal candidates will have:
- A Master's or PhD in a quantitative discipline
- At least 3 years of relevant experience
- Proficiency in Python
This position offers a hybrid work model with a competitive salary up to £100,000 plus bonus.
Quantitative Analyst – Asset-Backed Finance (Hybrid, London) employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst – Asset-Backed Finance (Hybrid, London)
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and data science sectors on LinkedIn. We can leverage our connections to get insights about the company and even potential referrals.
✨Tip Number 2
Prepare for those interviews! Brush up on your Python skills and be ready to discuss your quantitative models. We should practice common interview questions and even do mock interviews to boost our confidence.
✨Tip Number 3
Showcase your projects! If you've built any relevant models or conducted significant analyses, make sure to highlight them in discussions. We can create a portfolio that demonstrates our expertise and problem-solving abilities.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. We can keep an eye on new openings and apply as soon as they go live to stay ahead of the competition.
We think you need these skills to ace Quantitative Analyst – Asset-Backed Finance (Hybrid, London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in quantitative analysis and data science. We want to see how your skills align with the role, so don’t be shy about showcasing your Python proficiency and any projects that relate to asset-backed finance.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your background makes you a perfect fit for our Credit & Asset-Backed Finance team. Keep it concise but impactful!
Showcase Your Analytical Skills: In your application, include examples of how you've built quantitative models or conducted data analysis in previous roles. We love seeing real-world applications of your skills, so don’t hold back on the details!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at Jobster
✨Know Your Numbers
Brush up on your quantitative skills and be ready to discuss specific models you've built or data analyses you've conducted. Be prepared to explain your thought process and the impact of your work on investment decisions.
✨Python Proficiency is Key
Since proficiency in Python is a must, make sure you can demonstrate your coding skills. Consider preparing a small project or example that showcases your ability to manipulate data and build models using Python.
✨Research the Firm
Familiarise yourself with the investment firm's portfolio and recent projects in Credit & Asset-Backed Finance. This will not only help you answer questions but also allow you to ask insightful questions that show your genuine interest in their work.
✨Prepare for Scenario Questions
Expect scenario-based questions where you might need to analyse a hypothetical situation or dataset. Practise articulating your approach to problem-solving and how you would apply your quantitative skills in real-world scenarios.
