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Quantitative Trader
Overview
Quantitative traders apply quantitative methods to assess financial markets or products. They use mathematical models to identify trading opportunities, and buy and sell stocks and bonds.
Description
- Extract and discover patterns in price data to identify trends and anomalies from large datasets.
- Identify profitable trading opportunities by applying mathematical models and statistical analysis.
- Design and implement high-frequency trading algorithms focused on crypto markets for rapid trade execution.
- Create tools for data analysis of patterns, enabling a deeper understanding of market dynamics and behaviour.
- Develop and fine-tune exchange simulators to test trading strategies under various market scenarios before real implementation.
Entry requirements
- You'll need at least a Degree in any hard sciences field such as Computer Science, Physics, Mathematics, Statistics, or Data Science.
- Having in-depth knowledge of mathematical terms like skewness, conditional probability, kurtosis, and VaR (Value at Risk) will give you a strong foundation for success.
Salary
$4,900 – 9,500
/mo
Salary ranges are estimated based on public information found on Singaporean job portals, including MyCareersFuture, MySkillsFuture. Updated as of 2026.
Trivia
Starting out as a data research analyst is a typical career path for quantitative traders. To give themselves a head start, some even take a Master's Degree in Financial Engineering to further hone their hard skills.
What to expect
You'll be continually working with complex data when analysing results and implementing trade strategies. Strong analytical skills are essential.
Soft
skills
Risk-Taking
Ability to make calculated decisions in uncertain financial markets.
Innovative Problem-Solving
Skilled in finding creative solutions to complex trading challenges and adapting to changing market conditions.
High-Stress Tolerance
Able to remain calm and make quick decisions in fast-paced trading environments.
Strong Mathematical Skills
Skilled in analysing financial data and developing complex trading algorithms.
Programming Proficiency
Familiarity with C++, Java, Python and Perl to create and implement trading models and algorithms.
Financial Markets Knowledge
Deep understanding of market dynamics, trading strategies, and financial instruments across various asset classes.
Hard
skills
"A good Trader makes decisions and takes calculated risks based on the knowledge that they have."
Bryan, Theme International Trading, Quantitative Trader
National Youth Council
Frequently asked questions
Yes, it is. The trading world is dynamic and quantitative traders have to be prepare for risks constantly. Even the most novel concepts that used to reap profits may result in major losses the next day, so it is necessary for quantitative traders to adapt and keep looking for unique strategies and opportunities for profit.
High-frequency trading uses computer programmes to transact a large number of orders within seconds. This is done using complex algorithms that analyse and execute orders based on certain market conditions.
One of the biggest risks in quantitative trading is that it is based on historical data. If the data is wrong, it would lead to large losses.
Yes, algorithmic trading is legal. There are no rules or laws that limit the use of trading algorithms.