16 часов назад
Campus Quantitative Researcher (Intern) (Machine Learning)
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Описание вакансии
Текст:
TL;DR
Campus Quantitative Researcher (Intern) (Machine Learning): Building predictive trading models from big data and developing algorithms for automated execution across global financial exchanges with an accent on quantitative research, machine learning, statistics, and programming. Focus on designing automated trading strategies, testing models in live markets, and applying research across trading-team rotations.
Location: Hong Kong or Shanghai
Company
conducts quantitative research and develops technologies for global financial markets.
What you will do
- Build predictive trading models from large datasets.
- Develop algorithms for automated trade execution across financial exchanges.
- Apply quantitative research, programming, and trading knowledge during team rotations.
- Devise automated trading strategies and test them against market competition.
- Use large-scale computing resources to support research projects.
- Work with experienced quantitative researchers, traders, and developers under mentorship.
Requirements
- Be enrolled in or recently completing an undergraduate or graduate program.
- Demonstrate strong programming and/or quantitative analysis skills.
- Have a background in mathematics, computer science, statistics, physics, engineering, or another technical discipline.
- Show strong analytical ability, curiosity, and motivation to learn.
- Maintain reliable and predictable availability.
- Be interested in working in Hong Kong or Shanghai full-time after graduation.
Nice to have
- Experience with machine learning, data mining, statistics, Python, or C++.
- Previous knowledge of finance or trading is not required.
Culture & Benefits
- 10-week internship program with structured training.
- In-house courses covering trading, programming, quantitative research, and market mechanics.
- Trading simulations developed and delivered by experienced practitioners.
- Mentorship from quantitative researchers and traders during rotations and research projects.
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