Senior Data Scientist (Trust & Fraud)

Grab; Petaling Jaya; On-site; MYR 120,000 - 180,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

GrabFlex benefits

Parental leave

Birthday leave

LASA volunteering leave

Grabber Assistance Programme

Job summary

Grab is seeking a data science professional to fight fraud by analyzing transactional data and deploying scalable ML models. You will work as an Individual Contributor in a full-time, on-site role at the Petaling Jaya office, collaborating with product and software teams to push ML and LLM capabilities at scale.

You will design, train, and fine-tune model architectures using tools such as Graph Neural Networks, Transformers, and open-source LLMs, while improving data pipelines and automation.

Qualifications

• Degree in a quantitative field (e.g., CS, physics, maths).
• 3+ years of Python/SQL and data processing experience.
• Hands-on ML model development with common libraries.
• Experience with DL architectures and ML techniques.

Responsibilities

• Analyze transactional data to detect fraud with ML.
• Develop and deploy models, ensuring seamless integration.
• Collaborate with cross-functional teams across the lifecycle.
• Research advancements in algorithms and AI for fraud defence.
• Build and maintain high-fidelity training datasets and synthetic data.

Skills

Python

SQL

Spark

TensorFlow

PyTorch

XGBoost

LightGBM

Scikit-learn

Transformers

RAG

LangGraph

LangChain

Claude subagents

Education

Bachelor's degree in Computer Science/Physics/Statistics/Mathematics/Engineering/Economics

Tools

Graph Neural Networks

Transformers

GPT/LLM frameworks

Open-source LLMs (Qwen)

Job description

Get to Know Our Team

We are the architects of trust. Our mission is to shield the Grab ecosystem from evolving fraud and safety threats by turning massive datasets into applicable intelligence. From deploying sequence-based models for payment risk to applying graph algorithms that unmask complex money laundering networks, we operate at the intersection of deep learning and platform security. We don't just react; we innovate, researching the latest methods to neutralise tactics before they even surface.

Get to Know the Role

You will fight fraud by analysing transactional data, developing and deploying machine learning models, and collaborating with cross-functional teams to ensure the seamless integration of fraud detection systems. Reporting to the Data Science Manager II, you will work as an Individual Contributor in a full-time, on-site role at our office in Petaling Jaya, Malaysia. In this role, you will push the boundaries of machine learning and LLM applications at a massive scale, growing your expertise in cutting-edge agentic systems.

The Critical Tasks You Will Perform

• You will partner with teams to architect scalable data science solutions that translate complex operational challenges into strategic wins, integrating both traditional ML and agentic LLM systems.
• You will conduct cutting-edge research to incorporate the latest advancements in algorithms and generative AI into our defense systems to actively counter emerging fraud tactics.
• You will master data orchestration by preparing, augmenting, and combining diverse data types to build high-fidelity training datasets, including using LLMs to generate synthetic data and labels.
• You will design, train, and fine-tune model architectures, utilizing a toolkit that includes Graph Neural Networks (GNNs), Transformers, fine-tuned open-source LLMs (like Qwen), and Gradient Boosted Trees.
• You will lead the end-to-end lifecycle of your models-from production deployment to performance monitoring-iterating alongside software and product engineering teams.
• You will leverage Generative AI tools (like coding assistants and analytical co-pilots) in your daily workflows to accelerate code generation, automate testing, and enhance your overall productivity.

The Essential Skills You Will Need

• You hold a degree in Computer Science, Physics, Statistics, Mathematics, Engineering, Economics, or a related quantitative field.
• You have at least 3 years of experience with proficiency in Python and SQL, alongside practical experience using distributed engines like Spark to wrangle and process large-scale datasets.
• You have hands‑on experience building and deploying machine learning models using standard libraries such as TensorFlow, PyTorch, XGBoost, LightGBM, or Scikit‑learn.
• You have practical experience with deep learning architectures (Transformers, RNNs, CNNs) and traditional ML (Boosted Trees), demonstrating the ability to choose the optimal architecture for specific problems.
• You have an understanding of LLM and Agentic system foundations (e.g., RAG, Transformers) and hands‑on experience building or using frameworks like LangGraph, LangChain, or Claude subagents.
• You have experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.

Life at Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex, create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.

What we stand for at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.