Quantitative Trader

LUDISIA (CAYMAN) LTD. Singapore Branch; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

A leading trading firm in Singapore is seeking a Quantitative Trader to enhance its trading team. The ideal candidate will design and implement high-frequency trading algorithms and analyze market data. This role requires strong programming skills in C++ and Python, along with a relevant academic background, enabling the development of sophisticated trading strategies.

Qualifications

• At least a Bachelors Degree from a top-tier university.
• Previous experience in high-frequency trading is advantageous.
• Strong programming and data analysis skills required.

Responsibilities

• Design and implement high-frequency trading algorithms.
• Analyze market data for patterns and insights.
• Develop tools for data analysis and contribute to analytical libraries.

Skills

Data Mining

Statistical Techniques

Programming in C++

Programming in Python

Back-Testing

Education

Bachelors Degree in Computing, Statistics, Mathematics

Job description

Ludisia (Cayman) Ltd. Singapore Branch seeks a Quantitative Trader to join one of our trading teams in Singapore. As a Quantitative Trader, you will be using in-house trading system—one of the fastest and most comprehensive in the world—to develop and deploy algorithmic trading strategies based on patterns in market behavior.

Responsibilities

• Designing, implementing, and deploying high-frequency trading algorithms
• Exploring trading ideas by analyzing market data and market micro-structure for patterns
• Creating tools to analyze data for patterns
• Contributing to libraries of analytical computations to support market data analysis and trading
• Developing, augmenting, and calibrating exchange simulators

Qualifications

• At least a Bachelors Degree in computing, statistics, mathematics or a related field from a top-tier university
• Previous internship or professional experience in high-frequency trading is advantageous
• Proficiency in back-testing, simulation, and statistical techniques (auto-regression, auto-correlation, and Principal Component Analysis)
• Solid data-mining and analysis skills, including experience dealing with a large amount of data/tick data
• Good experience with signal generation and statistical models
• Strong programming skills in C++ and Python