At a Glance
- Tasks: Solve complex trading problems using maths, computer science, and finance.
- Company: Join Goldman Sachs' innovative Strats team in London.
- Benefits: Competitive salary, dynamic work environment, and career advancement opportunities.
- Other info: Fast-paced environment with opportunities to work on cutting-edge projects.
- Why this job: Make a real impact in trading tech while collaborating with top professionals.
- Qualifications: Strong quantitative skills and a passion for finance and technology.
The predicted salary is between 63000 - 77000 £ per year.
Goldman Sachs’ Strats team in London is seeking highly capable quantitative researchers who combine mathematics, computer science and finance to solve complex problems on trading and risk platforms.
Strats develop pricing models, automate trading and build large-scale distributed systems used across desks. The role emphasizes collaboration with traders, clients and technologists in a fast-paced environment.
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Quantitative Desk Strategist - Trading Tech & Markets in London employer: Goldman Sachs
Goldman Sachs is an exceptional employer, offering a dynamic work environment in the heart of London where innovation and collaboration thrive. Employees benefit from comprehensive professional development opportunities, a strong emphasis on diversity and inclusion, and the chance to work with some of the brightest minds in finance. With a commitment to client success and a culture that fosters growth, joining Goldman Sachs means being part of a prestigious firm that values your contributions and supports your career aspirations.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Desk Strategist - Trading Tech & Markets in London
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We think you need these skills to ace Quantitative Desk Strategist - Trading Tech & Markets in London
Some tips for your application 🫡
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
