Lead Data Scientist

 

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

 

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'll fight fraud by analysing 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.

Reporting to the Data Science Manager II, you will work as an Individual Contributor in a Full-time role on-site at our office in Bangalore.

 

The Critical Tasks You Will Perform:

• Problem Architecting: Partner with teams to translate complex operational challenges into scalable data science solutions that align with Grab's strategic goals.
• Cutting-Edge Research: Stay at the forefront of the industry. You will research and incorporate the latest advancements in AI to counter fraud tactics.
• Data Orchestration: Master data preparation and augmentation, combining diverse data types to build high-fidelity datasets for model training.
• Model Innovation: Design, train, and fine-tune models. Your toolkit will include Graph Neural Networks (GNNs), Transformers/Sequence models, fine-tuned LLMs, and Boosted Trees.
• Production & Scale: Lead the end-to-end lifecycle of your models—from deployment into production to performance monitoring and iterative improvement alongside our software and product engineers.

 

The Essential Skills You Will Need:

• Education: A degree in Computer Science, Physics, Statistics, or a related quantitative field.
• Programming & Big Data: 8 or more years of experience with proficiency in Python and SQL, with experience using modern approaches like Spark or similar engines to wrangle and process large-scale datasets. Comfortable in writing clean, modular code.
• Machine Learning Experience: At least 4 years of hands-on experience building and deploying models using standard libraries such as TensorFlow, PyTorch, XGBoost, LightGBM, or Scikit-learn.
• Knowledge of Model Architectures: Experience with traditional ML, such as Boosted Trees. Additionally, exposure to some deep learning architectures, including Transformers, RNNs, or CNNs, along with the ability to choose the right approach for the problem at hand.
• LLM Foundations: A practical understanding of the LLM ecosystem. This includes how Transformers work and how to use tools like RAG (Retrieval-Augmented Generation). The goal is to enhance daily workflows or product features.

 

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.

 

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