Data Science Intern

Duration: 6 months (Full-time)

Location: Kuala Lumpur, Malaysia

Target: Final-year (4th year) undergraduates in Data Science, AI, CS, Engineering

About TrustDecision

TrustDecision is a leading global fintech risk intelligence company delivering AI-driven solutions

for credit risk, payment fraud, and digital trust to enterprises worldwide. The company serves

large financial institutions and internet platforms across Asia and beyond, applying advanced

machine learning to high-volume, real-time decisioning systems. TrustDecision is rapidly ex-

panding its presence in South East Asia, building local teams to support regional clients and

innovation.

Role Overview

This internship provides hands-on experience in fintech risk modelling, where interns work with

the Data Science team on credit risk or payment risk problems used in real production systems.

Key Responsibilities

• Analyse large-scale transactional and behavioural datasets using SQL and Python

• Build, test, and evaluate machine learning models for credit or payment risk

• Perform feature engineering, data validation, and performance analysis

• Investigate fraud patterns, model errors, and stability issues

• Communicate technical findings clearly to team members

Required Qualifications

• Final-year undergraduate in Data Science, AI, Computer Science, or Engineering

• Proficiency in Python for data analysis and modelling

• Ability to write SQL queries for data extraction and analysis

• Understanding of basic machine learning methods and evaluation metrics

• Strong analytical and problem-solving skills

• Fluent in both Chinese and English

Nice-to-Have Skills

• Exposure to deep learning frameworks such as PyTorch or TensorFlow

• Familiarity with big data tools such as Spark or distributed computing

• Coursework or projects related to fintech, risk, or fraud analytics

What You Will Gain

• Real-world experience working on production fintech risk models

• Mentorship from experienced data scientists and AI practitioners

• Exposure to large-scale data and industry-grade ML workflows

• Strong preparation for careers in data science, AI, or fintech

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