
Data-Driven Digital Asset Trader
6 days ago
We are seeking an intern to contribute to our team of researchers and engineers focused on developing innovative solutions for digital asset traders and researchers.
As a Quantitative Trading Intern, you will be part of a dynamic startup environment where you can learn from experienced professionals and contribute to high-impact projects.
The ideal candidate will have a strong foundation in mathematics, statistics, or econometrics, as well as programming experience in Python, R, MATLAB, or related tools.
Key responsibilities include conducting research on cryptocurrency markets, developing algorithmic trading strategies, analyzing large datasets, and collaborating with engineers to integrate research into production systems.
Additionally, you will support the development of risk management and portfolio optimization models, and contribute to the creation of research reports and visualizations to communicate findings to stakeholders.
To succeed in this role, you should have strong analytical and problem-solving skills, as well as clear communication and presentation abilities.
Requirements:
• Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Mathematics, Econometrics, Computational Finance, Physics)
• Strong foundation in mathematics, statistics, or econometrics (e.g., probability, linear algebra, calculus)
• Programming experience in Python, R, MATLAB, or related tools
• Familiarity with cryptocurrency markets and trading concepts
• Experience with data libraries such as pandas, numpy, scipy, and statistical modeling techniques
• Interest in time series analysis and algorithmic trading strategies
• Strong analytical and problem-solving skills
• Clear communication and ability to present research findings effectively
Benefits:
As a member of our team, you will have opportunities for professional growth, collaboration with experienced professionals, and contributions to high-impact projects. We encourage passionate and motivated individuals to apply.
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