обновлено 5 дней назад
Campus Quantitative Researcher (M1/M2 Intern) (Fintech)
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Описание вакансии
Текст:
TL;DR
Campus Quantitative Researcher (Fintech): Building predictive models from big data and developing algorithms for automated trading in global financial exchanges with an accent on quantitative analysis and software development. Focus on designing signal generation processes, implementing machine learning models, and optimizing execution algorithms.
Location: London or Paris
Company
conducts research in mathematics, physics, and computer science and applies it to global financial markets.
What you will do
- Build predictive models from big data for financial market research.
- Develop algorithms that automatically execute trades across global exchanges.
- Complete an intensive research project with mentorship from a trading team.
- Participate in training covering trading, programming, quantitative analysis, machine learning, C++, statistics, and market mechanics.
- Rotate across trading teams and contribute to projects with quant researchers, traders, and developers.
Requirements
- Currently studying in an M1/M2 program at a French school requiring a research internship, such as Ecole Polytechnique.
- Strong programming and/or quantitative analysis skills, including statistics, data mining, mathematics, or machine learning.
- Strong motivation to learn, improve, and work with feedback from competitive markets.
- Reliable and predictable availability throughout the internship.
- Prior finance or trading knowledge is not required.
Nice to have
- Training in computer science or mathematics.
- Exceptional achievement in a technical discipline such as electrical engineering, physics, neuroscience, materials science, or operations research.
- Entrepreneurial spirit and curiosity about quantitative research.
Culture & Benefits
- Work closely with experienced researchers, traders, developers, and mentors.
- Receive in-house training developed and delivered by specialists.
- Explore a blend of quantitative research, data science, trading, and software development.
- Research topics can be tailored to specific interests or academic requirements.
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