About the job:
My client a leading buy-side multi-manager are looking to bring in an experienced Quantitative Strategist profile to join one of their most established teams. As part of this role you will be responsible for all aspects statistical modelling for financial securities, with a focus on FX derivatives as well as providing quantitative support and strategy insight to discretionary and systematic PM's.
Responsibilities:
- Create user-friendly tools, that serve as interfaces for internal analytics models.
- Conduct research and develop models for pricing, risk assessment, and profit and loss (P&L) analysis of financial securities and derivatives.
- Developing libraries using C++ and Python.
- Work with Bloomberg and other data APIs to integrate and utilize financial data.
- Perform empirical modelling of financial securities within the frameworks of data science and statistical learning.
- Provide support to portfolio management teams concerning quantitative modelling issues.
Qualifications:
- Minimum of 6 years of expertise in financial quantitative analytics within a front-office or buy-side context.
- Hold an MSc or PhD from a reputable university in a STEM field.
- Possess intellectual maturity and a deep scientific understanding with a focus on data science and AI.
- Demonstrate exceptional familiarity with front-office pricing and risk models across multiple asset categories.
- Have developed models for pricing derivatives related to FX, options or volatility.
- Show proficiency in data-driven and statistical modeling of financial securities.
- Have practical experience collaborating directly with front-office traders, quants, and risk managers.
- Proficient development skills in C++, Python, and Excel.
- Exhibit a keen ability to quickly grasp new concepts, models, and technologies.
- Capable of working autonomously and delivering high-quality results within stringent timeframes.
How to Apply: Interested candidates are invited to submit their resume, detailing their relevant experience and qualifications
