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- Tasks: Join our team to develop and implement quantitative models for equity derivatives.
- Company: LA International is a leading global IT consultancy with award-winning recognition.
- Benefits: Enjoy hybrid working, competitive rates, and opportunities for professional development.
- Why this job: Make a real impact in Capital Markets while gaining hands-on experience with cutting-edge technology.
- Qualifications: Masters or PhD in Mathematics/Computer Science; strong programming skills in Python and C++ required.
- Other info: This is a 6-month contract with potential for growth in a dynamic environment.
The predicted salary is between 48000 - 72000 £ per year.
6 Month contract initially
Based: Hybrid/London - Max 2 days p/w onsite
Rate: Market rates (via Umbrella company)
We have a great opportunity with a world leading organisation where you will be provided with all of the support and development to succeed. A progressive organisation where you can really make a difference. We have a great opportunity for a number of Quant Analysts on a great program of work. This role provides an excellent opportunity to work on critical projects in the Capital Markets space, gain experience working with Front End teams and gain on-job learning of new technology & tools to deliver work.
The successful candidate will be a member of The clients QA Equity & Hybrid Products team, which is part of the Global Quantitative Analytics group (QA) and is responsible for research, development and implementation of quantitative models for the equity derivatives business. It covers equity flow products, equity structured & hybrid products, quantitative index and strategies business.
Key Responsibilities:- Documentation, Testing and improvements of an internal risk model, which is owned by The QA Equity & Hybrid Products team and feeds the Credit Valuation Adjustment (CVA) for products sensitive to future implied volatility dynamics (e.g. Corridor Variance Swaps).
- Liaise with Front Office, Technology and Model Validation teams, to deploy the risk model to production.
- Ideally possess a Masters or PhD in Mathematics/Computer Science or related field.
- Mathematically minded (knowledge of financial mathematics, ability to program numerical algorithms in C++).
- Experience in Front Office & Derivatives modelling.
- Theoretical knowledge of financial engineering/structuring and financial product development.
- Strong analytical and numerical skills.
- Good Python programming skills.
- Strong C++ programming skills (ideally worked in a C++ shared library).
- Able to explain complex ideas in a clear and coherent manner to colleagues/traders/sales/management both oral, written or in presentation.
- Integrity, desire to have correct and robust mathematical models and implementation.
This is an excellent opportunity on a great project of work. If you are looking for your next exciting opportunity, apply now for your CV to reach me directly, we will respond as soon as possible.
Contact Detail:
LA International Computer Consultants Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative analysis and financial modelling. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the Capital Markets space, especially those who work with equity derivatives. Attend relevant industry events or webinars to make connections that could lead to referrals.
✨Tip Number 3
Brush up on your C++ and Python programming skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects to demonstrate your coding abilities.
✨Tip Number 4
Prepare to discuss your experience with risk models and quantitative strategies in detail. Be ready to explain complex concepts clearly, as communication is key when liaising with Front Office and other teams.
We think you need these skills to ace Quant Analyst
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the key responsibilities and required skills. Highlight your relevant experience in quantitative analysis, programming, and financial mathematics.
Tailor Your CV: Customise your CV to reflect the specific skills and experiences that align with the Quant Analyst position. Emphasise your educational background, particularly if you have a Masters or PhD in Mathematics or Computer Science.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for quantitative analysis and your understanding of the Capital Markets space. Mention any relevant projects or experiences that demonstrate your analytical and programming skills.
Highlight Technical Skills: Make sure to clearly list your programming skills, especially in Python and C++. Provide examples of how you've used these skills in previous roles or projects, particularly in relation to financial modelling or risk assessment.
How to prepare for a job interview at LA International Computer Consultants Ltd
✨Brush Up on Financial Mathematics
Make sure you have a solid understanding of financial mathematics, especially concepts related to equity derivatives. Be prepared to discuss how these concepts apply to the role and demonstrate your knowledge during the interview.
✨Showcase Your Programming Skills
Since strong C++ and Python skills are essential for this position, be ready to talk about your programming experience. You might even be asked to solve a coding problem or explain your approach to numerical algorithms, so practice articulating your thought process.
✨Prepare for Technical Questions
Expect technical questions related to quantitative models and risk management. Review common models used in equity derivatives and be prepared to explain their applications and limitations. This will show your depth of knowledge and analytical skills.
✨Communicate Clearly
As the role requires explaining complex ideas to various stakeholders, practice conveying technical information in a clear and concise manner. Consider preparing examples from your past experiences where you successfully communicated complex concepts to non-technical colleagues.
