
Quantitative Strategist
at Qube
Posted 3 hours ago
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- Compensation
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**Quantitative Strategist at Qube Research & Technologies (QRT):** Lead data-driven strategy, delivering high-quality analytics to senior management. Develop risk management tools, share trading expertise with cross-functional teams, and enhance portfolio management. Must-have: Advanced degree in quantitative field, coding skills, trading experience, and fluency in Python/R. Experience working with big data and financial markets. Collaborative, innovative mindset. Senior-level role.
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT
- Your core objective is to deliver high quality analytics of trading and production data and provide senior management with strategic outputs
- Develop new reports and analysis tools in order to help traders and researchers manage their risk on a daily basis
- Leverage your trading and market expertise by sharing production results and methodology with other traders and researchers
- Contribute to portfolio management through periodic strategic deep dives and improved continuous monitoring
Your present skillset
- Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering
- Coding skills required in at least one programming language (e.g. Python + SQL, VBA) and capacity to work on large datasets
- Experience in finance is a plus
- Excellent communication skills
Your enhanced experience and learning opportunities at QRT
- Mentorship from industry professionals
- Detailed practical hands-on experience with portfolio management and analysis
- Contribution to high level decision making on global businesses
- Exposure to large scale data analysis technology
- Experience in a collaborative and collegial corporate environment
