Intern, Data Scientist (Integrity)

Descripción del puesto:

Job Description

Get to Know the Team
The Grab Integrity team is dedicated to protecting the Grab platform from multiple types of fraud and safety incidents. Our team uses rich datasets ranging from payment risk prediction using sequence-based models to detecting money laundering with graph algorithms and ensuring platform safety. We research new methods to stay ahead of latest fraud tactics, contributing to the creation of thoughtful and secure products.
Get to Know the Role
You'll fight fraud by analyzing transactional data, developing and deploying machine learning models, and collaborating with teams to ensure seamless integration of fraud detection systems. You'll help keep our platform safe and trustworthy.
This will be a paid internship role, where you will have a dedicated mentor to guide you through the learning, building and creating value during your internship.
You will report to our Head of Data Science, FinTrust and FinID. This role will be based onsite at our office in Petaling Jaya, Selangor.
The Critical Tasks You Will Perform
* Collaborate with your team to understand and convert operational issues into data science problems, aligning efforts with our strategic goals.
* Stay updated with the latest research and advancements in the field, incorporating the latest models and techniques to address new fraud tactics.
* Handle data preparation and augmentation, using multiple data types to create comprehensive datasets for model training.
* Train and improve machine learning models, ensuring accuracy and efficiency in fraud detection through careful selection and tuning of algorithms. Types of algorithms the team work on include Graph Neural Networks, Transformer/ Sequence models, finetuned LLMs, Boosted Trees
* Deploy models into production, managing their performance, and working with data scientists, software engineers, and product managers to ensure seamless integration and ongoing improvements

Requerimientos del candidato/a:

Qualifications

What Essential Skills You Will Need
* Can start from May 2026 onwards with a minimum duration of 3 months
* Study for a degree in computer science, physics, statistics, or a related quantitative field.
* Proficiency in Python, SQL, and programming skills, with familiarity with numeric libraries, containers, and modular software design
* Some experience of standard machine learning libraries such as TensorFlow, PyTorch, XGBoost, LightGBM, and Scikit-learn
* Understand and some experience using traditional ML techniques like Boosted Trees, and deep neural network architectures, like CNNs, RNNs, Transformers
* Familiarity with LLM coding tools, e.g. Cursor, Claude code, or have some experience using LLMs for improving coding efficiency