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For Companies At a Glance
- Tasks: Design and implement quantitative models for trading strategies in a dynamic financial environment.
- Company: Goldman Sachs is a leading global investment banking and securities firm with a commitment to diversity.
- Benefits: Enjoy professional growth opportunities, wellness programs, and a supportive work culture.
- Why this job: Join a team that values innovation and collaboration while making impactful decisions in finance.
- Qualifications: Advanced degree in a relevant field and strong programming skills required; 4+ years of experience preferred.
- Other info: Remote work options and a focus on personal development make this role unique.
The predicted salary is between 43200 - 72000 £ per year.
The Quantitative Engineer will be responsible for the design, development, and implementation of quantitative models and algorithms for a financial services company. This individual will work closely with portfolio managers and other stakeholders to identify areas where quantitative analysis can provide insights and support decision-making.
Key Responsibilities:
- Develop and implement quantitative models and algorithms to support trading and investment strategies.
- Collaborate with traders, portfolio managers, and other stakeholders to identify areas where quantitative analysis can provide insights and support decision-making.
- Lead the development of proprietary models and algorithms to support the company's trading and investment strategies.
- Communicate results and findings to stakeholders in a clear and concise manner.
- Stay current with industry developments and new technologies.
Qualifications:
- Advanced degree in a related field such as Mathematics, Physics, Computer Science, Financial Engineering or a related field.
- Strong programming skills in at least one language such as Python, R, C++ or Java.
- Strong understanding of mathematical and statistical concepts, especially in finance.
- Strong problem-solving skills and the ability to think critically.
- Excellent communication skills and the ability to work well in a team environment.
- Strong experience in financial markets, risk management and time series analysis.
Experience:
- Minimum of 4+ years of experience in a quantitative role in a financial services company.
- Experience with financial modelling or in the financial industry is a must.
- Background in equity or credit preferred.
- Full stack development or Secdb/Slang experience preferred.
Quantitative Engineer - Vice President - AMD Private - London employer: Quality Control Specialist - Pest Control
Contact Detail:
Quality Control Specialist - Pest Control Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Engineer - Vice President - AMD Private - London
✨Tip Number 1
Network with professionals in the financial services industry, especially those working in quantitative roles. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and learn about the latest trends and technologies.
✨Tip Number 2
Showcase your programming skills by contributing to open-source projects or creating your own quantitative models. This not only demonstrates your technical abilities but also your passion for the field, making you a more attractive candidate.
✨Tip Number 3
Stay updated on the latest developments in quantitative finance and algorithmic trading. Follow relevant blogs, podcasts, and research papers to ensure you can discuss current trends and innovations during interviews.
✨Tip Number 4
Prepare to articulate your problem-solving process and critical thinking skills. Be ready to discuss specific examples from your past experience where you successfully applied quantitative analysis to support decision-making in a financial context.
We think you need these skills to ace Quantitative Engineer - Vice President - AMD Private - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative roles, particularly in financial services. Emphasise your programming skills in languages like Python or R, and showcase any experience with financial modelling or risk management.
Craft a Strong Cover Letter: In your cover letter, explain why you are interested in the Quantitative Engineer position at Goldman Sachs. Discuss how your background in mathematics, statistics, or computer science aligns with the job requirements and how you can contribute to their trading and investment strategies.
Showcase Problem-Solving Skills: Provide examples in your application that demonstrate your strong problem-solving abilities. Highlight specific projects or challenges you've faced in previous roles and how you successfully addressed them using quantitative analysis.
Prepare for Technical Questions: Be ready to discuss your technical skills and knowledge during the interview process. Brush up on mathematical and statistical concepts relevant to finance, and be prepared to solve problems or answer questions related to quantitative models and algorithms.
How to prepare for a job interview at Quality Control Specialist - Pest Control
✨Showcase Your Technical Skills
As a Quantitative Engineer, you'll need to demonstrate your strong programming skills. Be prepared to discuss your experience with languages like Python, R, C++, or Java, and consider bringing examples of your work or projects that highlight your technical abilities.
✨Understand Financial Concepts
Make sure you have a solid grasp of mathematical and statistical concepts, especially as they relate to finance. Brush up on key topics such as financial modelling, risk management, and time series analysis, as these will likely come up during the interview.
✨Prepare for Problem-Solving Questions
Expect to face problem-solving scenarios that test your critical thinking skills. Practice articulating your thought process clearly and concisely, as this will be crucial when collaborating with traders and portfolio managers.
✨Communicate Effectively
Strong communication skills are essential for this role. Be ready to explain complex quantitative models and findings in a way that is understandable to stakeholders who may not have a technical background. Practising how you present your ideas can make a big difference.
