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- Tasks: Lead the design and development of quantitative models for the QIS business.
- Company: Join UBS, a leading global financial services firm in London.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborate with diverse teams for effective risk management.
- Why this job: Make an impact with large-scale data and advanced analytics in finance.
- Qualifications: 3+ years in systematic trading or quantitative research, strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
UBS is seeking a quantitative analyst in London to lead the design, development, and implementation of quantitative models for the QIS business. The candidate should have 3+ years in systematic trading or quantitative research, strong proficiency in Python, and a solid grounding in financial mathematics.
Key responsibilities include:
- Delivering high-quality applications
- Collaborating with various teams for effective risk management
The role offers an opportunity to work with large scale data and advanced analytics within a dynamic environment.
QIS Quant: Front-Office Modeling, Python & Cloud in London employer: UBS
Contact Detail:
UBS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land QIS Quant: Front-Office Modeling, Python & Cloud in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at UBS or similar firms. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or contributions to open-source Python libraries, make sure to highlight them. This is your chance to demonstrate your expertise in quantitative modelling and financial mathematics.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python coding skills and be ready to tackle real-world problems. Practice explaining your thought process clearly, as collaboration is key in this role.
✨Tip Number 4
Apply through our website! We make it easy for you to showcase your talents directly to us. Plus, it shows you're genuinely interested in being part of our team at UBS.
We think you need these skills to ace QIS Quant: Front-Office Modeling, Python & Cloud in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your proficiency in Python in your application. We want to see how you've used it in previous roles, especially in systematic trading or quantitative research.
Quantitative Experience is Key: Don’t forget to mention your experience in quantitative analysis and financial mathematics. We’re looking for someone with at least 3 years in the field, so let us know what you’ve achieved!
Tailor Your Application: Take a moment to customise your application for this role. We love seeing candidates who understand our needs and can demonstrate how their skills align with the responsibilities outlined in the job description.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at UBS
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss specific projects where you've used Python for quantitative analysis or model development. Practising coding challenges can also help you demonstrate your proficiency.
✨Brush Up on Financial Mathematics
Since the role requires a solid grounding in financial mathematics, review key concepts and be prepared to explain how you've applied them in your previous work. This could include topics like stochastic calculus or risk management techniques.
✨Showcase Your Collaborative Spirit
Collaboration is key in this role, so think of examples where you've worked with different teams. Be ready to discuss how you effectively communicated complex quantitative concepts to non-technical stakeholders.
✨Prepare for Data-Driven Discussions
Given the focus on large-scale data and advanced analytics, come prepared to talk about your experience with data handling and analysis. Highlight any tools or frameworks you've used and be ready to discuss how you approach data-driven decision-making.