Quantitative Strategy Researcher Intern(Deep Learning Focus)

About Matrixport

Founded in 2019, Matrixport is a global digital asset financial services platform bridging traditional finance and the digital asset ecosystem through technology and regulatory compliance. The company has grown into a unicorn with a valuation exceeding US$1 billion. Matrixport and its subsidiaries maintain a licensed and regulated footprint across major financial centres, including Singapore, Hong Kong, Switzerland, the United Kingdom, and the United States. Matrixport manages over US$7 billion in assets and offers institution-grade services spanning custody, wealth and yield management, structured products, and trading solutions. The firm focuses on building secure, compliant, and scalable digital financial services for global clients.

For more information, visit www.matrixport.com

Why Join Us

At Matrixport, we tackle complex problems as a team. We encourage openness and promote transparency, respect, and inclusivity. Every team member is valued and has a voice that can be heard. We are always in search of intellectually curious and entrepreneurial individuals who are keen on making an impact in the crypto ecosystem and in building a better product for the next one billion users.

ABOUT THE ROLE

Job Responsibilities:

1. Perform in-depth data mining and modeling to develop machine learning and medium/high-frequency trading strategies.
2. Track factor performance, conduct quantitative backtesting, simulation, and follow-up improvement work.

Requirements:

1. Strong learning ability, good at critical thinking, and capable of solving problems independently; strong curiosity and self-motivation.
2. Proficient in the optimization and iteration of machine learning (deep learning) models, and possessing innovative research capabilities.
3. Excellent programming skills, proficient in at least two programming languages, and skilled in using Tensorflow/Pytorch.
4. Preferred qualifications: Experience in numerical optimization and ability to quickly reproduce State-of-the-art results, OR having published relevant papers in top international conferences or journals (including but not limited to NIPS, ICML, CVPR, AAAI).
5. Master’s degree or higher (or an exceptionally outstanding Bachelor’s degree, prefer 985) in a Science or Engineering major. Preference is given to candidates with excellent achievements in top industry competitions or relevant quantitative strategy work/internship experience.

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