Job Description

We are looking for a highly organized Operations Assistant to support the Operations Associate in driving key initiatives and ensuring smooth day-to-day execution across the organization. This is a mid-level administrative role that requires strong attention to detail and adaptability in a fast-paced environment.

Responsibilities

• Support the account opening process across global banks, brokers, and digital asset platforms by preparing required documents and coordinating internal inputs
• Assist in managing annual compliance tasks for offshore entities and trading venues to help ensure smooth operations
• Ensure documentation and data are accurately filed, securely stored, and easily retrievable
• Track project progress and provide clear, concise status updates
• Handle administrative tasks such as preparing expense claims and arranging couriers
• Perform data entry, manage filing systems, and maintain internal records with accuracy
• Coordinate with other departments on routine operational tasks
• Conduct research and information gathering to support decision-making
• Provide other ad-hoc administrative support as assigned

Requirements

• Bachelor’s degree from a recognized institution
• Prior experience in administrative support, business operations, or customer service is preferred
• Strong attention to detail and organizational skills
• Effective written and verbal communication
• Responsible, trustworthy, and able to maintain confidentiality
• Proactive attitude with a willingness to learn
• Proficient in English and Mandarin for business communication

This role is directed at graduates seeking a July 2026 start date. 

What you can expect:

• Kickstart your journey with a focused training program to quickly get you up to speed with our systems and processes.
• Gain hands-on experience in real-life research projects  
• Enhance your analytical skills by working with large datasets provided by the company to uncover insights.
• Learn to prioritize key findings and turn them into actionable solutions.
• Take ownership of your ideas and contribute to innovative strategies from day one.
• Be part of an environment that encourages creativity, innovation, and exploration without boundaries.

Qualifications

• Bachelor’s or master's degree in a quantitative discipline (Computer Science, Math, Stats, Physics, Financial Engineering, Economics, or another highly quantitative field)
• Juniors with less than 3 years of experience in relevant fields are welcome to apply for this role
• Excellent problem-solving skills and proactiveness in an independent research environment
• Strong written and verbal communication skills fostering research discussion with various stakeholders
• Proficient in Python and can learn C++ quickly
• Proficient in ML techniques 

Why you should join us:

• Working at one of the most competitive quant trading firms in the crypto space. 
• Engaging projects offering accelerated responsibilities and ownership.
• Great company culture emphasizing Meritocracy, Urgency, Team, Integrity and Innovation 
• Competitive compensation

Location and Onboarding Requirement

• To ensure comprehensive onboarding and integration into our team, qualified overseas candidates will be required to attend the program at our HQ Taiwan office for a period of 12 months.
• Candidates are expected to onboard as batches, exact date will be further discussed

Role Overview

We are seeking highly motivated and curious individuals to join our Machine Learning team at Kronos Research. In this role, you will bridge the gap between advanced deep learning and financial markets, designing robust models for medium and high-frequency systematic trading strategies. You will manage the full ML lifecycle, from researching novel architectures to deploying scalable, low-latency models that directly drive trading revenue.

Key Responsibilities

• Feature Engineering: Analyze complex time-series data, orderbook dynamics and trade data to engineer high-signal features
• Deep Learning Architecture: Design and train deep-learning based models (MLP, LSTM, RNN, Transformers, RL agents, etc) tailored for financial trading environments
• Backtesting & Evaluation: Conduct comprehensive backtesting and simulation across various asset classes and exchanges; analyze trade execution and PnL attribution
• Model Deployment: Collaborate with engineering teams to optimize and deploy models into production
• MLOps & Automation: Build and maintain automated pipelines for data ingestion, model retraining, and continuous performance monitoring to streamline the research-to-production workflow

Qualifications

• Strong academic or professional foundation in machine learning, quantitative research, and/or other related STEM fields; open to both experienced candidates and highly-motivated fresh graduates
• Deep understanding of neural network architectures and their application to time-series forecasting
• Proficiency in Python and modern ML frameworks (PyTorch/TensorFlow/Jax); C++ preferred
• Solid command of probability theory, linear algebra and applied statistics
• Strong communication skills and able to articulate technical concepts with clarity
• High level of drive, curiosity and a passion for continuously learning in a fast-paced environment

Role Overview

We are seeking highly motivated and curious individuals to join our Machine Learning team at Kronos Research. In this role, you will bridge the gap between advanced deep learning and financial markets, designing robust models for medium and high-frequency systematic trading strategies. You will manage the full ML lifecycle, from researching novel architectures to deploying scalable, low-latency models that directly drive trading revenue.

Key Responsibilities

• Feature Engineering: Analyze complex time-series data, orderbook dynamics and trade data to engineer high-signal features
• Deep Learning Architecture: Design and train deep-learning based models (MLP, LSTM, RNN, Transformers, RL agents, etc) tailored for financial trading environments
• Backtesting & Evaluation: Conduct comprehensive backtesting and simulation across various asset classes and exchanges; analyze trade execution and PnL attribution
• Model Deployment: Collaborate with engineering teams to optimize and deploy models into production
• MLOps & Automation: Build and maintain automated pipelines for data ingestion, model retraining, and continuous performance monitoring to streamline the research-to-production workflow

Qualifications

• Strong academic or professional foundation in machine learning, quantitative research, and/or other related STEM fields; open to both experienced candidates and highly-motivated fresh graduates
• Deep understanding of neural network architectures and their application to time-series forecasting
• Proficiency in Python and modern ML frameworks (PyTorch/TensorFlow/Jax); C++ preferred
• Solid command of probability theory, linear algebra and applied statistics
• Strong communication skills and able to articulate technical concepts with clarity
• High level of drive, curiosity and a passion for continuously learning in a fast-paced environment