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Metabit Technology LLC

Researcher - 2027 New Grad

Hong Kong

Location
Hong Kong
Work
Not stated
Employment
Not stated
Level
Entry level
Function
Science & research
Pay
Not stated
Posted
6 weeks ago

About the role

Job Responsibilities

If you are interested in statistics and data mining, you can participate in Feature Engineering research based on the company's self-developed ML/RL framework;

If you are interested in the application of ML/DL in AI quantitative analysis, you can participate in machine learning model research;

If you are interested in tools such as RL/Optimization, you can participate in portfolio optimization research;

If you are interested in knowledge in fields such as CV/NLP, you can participate in Alternative Alpha research;

If you are interested in models such as RL/Stochastic Processes, you can participate in order placement algorithms and impact models research;

In addition, you will collaborate with the engineering team to provide detailed and comprehensive requirements and code contributions for the company's self-developed distributed systems, data platforms, and trading systems. Your work will ultimately have a direct impact on our research and live trading.

Requirements

  • Grades from a World-Renowned University, majoring in Computer Science, Mathematics, Physics, Statistics, or other related STEM fields;
  • Familiarity with Linux environment, strong Python programming skills, and proficiency in Python scientific computing libraries;
  • Excellent probability and statistics skills, and rigorous research habits;
  • Good communication and logical thinking skills.

Bonus points:

  • Experience and outstanding results in competitions such as NOI, ICPC, CMO, CPhO, etc.;
  • Publication in top CS/Stats journals/conferences;
  • Kaggle ML competition winner;
  • Internship/work experience in a Prop Shop, Hedge Fund, or Tech company.

Source

Posted by Metabit Technology LLC on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 02:59 UTC; the original is the reference.

View the original ad ↗

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