Quantitative Research Intern (May 2027)

Iaas Lc; Singapore; On-site; SGD 17,000 - 23,000; Part time

Job summary

IMC invites you to join its Quant Research Internship in Singapore, where you will work at the intersection of data science, financial markets, and algorithmic trading, gaining hands-on experience under senior mentors.

You’ll train on trading concepts, develop predictive models, and present findings. A strong quantitative background and Python programming are essential; internship starts May/June 2027.

Qualifications

• Bachelor's, Master's or PhD in a highly quantitative field.
• Strong analytical and problem-solving skills.
• Proficient in programming, preferably Python; knowledge of C++, Java, MATLAB, or R.

Responsibilities

• Participate in an intensive training program covering trading concepts, theory, statistical modelling, and machine learning techniques.
• Tackle a meaningful research challenge—designing new predictive models, optimising existing strategies, or leveraging alternative data to extract insights.
• Explore large financial and market datasets, identify patterns, and develop quantitative models that contribute to trading decisions.
• Work closely with traders, researchers, and engineers in a fast-paced environment.
• Present findings through reports and presentations to both technical and non-technical audiences.

Skills

Python

C++

Java

MATLAB

R

Analytical thinking

Education

Bachelor's/Master's/PhD in Mathematics/Statistics/CS/Physics/Engineering

Tools

Python

Other languages (C++, Java, MATLAB, R)

Job description

IMC is a leading global trading firm that combines technology, advanced quantitative research, and cutting-edge machine learning techniques to trade a broad range of products globally. With a strong focus on innovation, we leverage quantitative models, highperformance computing, and a deep understanding of the markets todrive our trading decisions.

As a Quant Research Intern, you'll work at the intersection of data science, financial markets, and algorithmic trading, solving real-world challenges that drive our trading strategies. This internship program offers a unique opportunity to gain hands‑on experience in quantitative research, supported by structured learning, real‑world project work, and direct mentorship from senior IMC employees.

What You'll Do:

• Participate in an intensive training program covering trading concepts, theory, statistical modelling, and machine learning techniques.
• Tackle a meaningful research challenge - whether it's designing new predictive models, optimising existing strategies, or leveraging alternative data to extract actionable insights.
• Explore large financial and market datasets, identify patterns, and develop quantitative models that contribute to our trading decisions.
• Work closely with traders, researchers, and engineers in a fast-paced, intellectually stimulating environment.
• Present your findings through reports and presentations, gaining exposure to both technical and non-technical audiences.

What You'll Learn:

• A deep understanding of finance, trading, market structure, data, and quantitative research methodologies.
• Hands‑on experience with data science techniques and programming in Python.
• Exposure to real-time problem-solving in a quantitative trading environment.
• The ability to present research findings and work collaboratively with cross disciplinary teams.

Your Skills and Experience:

• Currently pursuing a bachelor's, master's, or PhD in a highly quantitative field, such as Mathematics, Statistics, Computer Science, Physics, Engineering, or a related discipline.
• Strong analytical and problem‑solving skills, with a keen interest in applying mathematical and statistical techniques to real‑world challenges.
• Proficient in programming, preferably in Python, or other relevant languages like C++, Java, MATLAB, or R.
• Curious and driven, with a passion for learning, adapting, and innovating in a fastpaced trading environment.
• Excellent communication skills, with the ability to distil complex concepts into clear, actionable insights.
• Must be able to start the internship in May/June 2027.