Quantitative Strategy Researcher (Deep Learning Focus)

About Matrixport

Founded in 2019, Matrixport is a global hub for cryptocurrency financial services. Valued at more than US$1 billion, the company, through its subsidiaries, holds regulatory licenses across major markets, including Singapore, Hong Kong, Switzerland, the United Kingdom, and the United States. Matrixport operates seven offices worldwide, manages more than US$7 billion in assets under management and custody, processes more than US$7 billion in monthly trading volume, and has paid out more than US$2 billion in interest to date. Its suite of digital asset financial solutions is designed to help clients maximize capital efficiency and achieve sustainable asset growth.

Through its local subsidiaries, Matrixport has received trust or company service provider and money lender licenses in Hong Kong, as well as a FINMA asset management license in Switzerland. The company operates as an appointed representative in the United Kingdom, is registered as a money services business in the United States, and is a member of Switzerland’s FINMA SRO-VFQ. In Singapore, its subsidiary Fly Wing holds a Major Payment Institution license from the Monetary Authority of Singapore. Matrixport has been named by CB Insights as one of the “50 Most Promising Blockchain Companies,” included in the Hurun “2024 Global Unicorn List,” and recognized as a fintech unicorn in Singapore in 2025.

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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