Senior Data Scientist

Company Description

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.

Job Description

Get to know our Team:

GrabFin is an aggregate of FinTech businesses spread across 6 countries in South East Asia, in the Payments, Lending and Insurance domains. Our engineering teams are stationed in Bangalore, Singapore, Indonesia and Vietnam. We are incredibly excited about the opportunity to provide innovative financial services to all participants of the Grab Ecosystem be it our Consumers, Drivers or Merchants. Our products are built on fundamental market insights combined with advanced Data Science, Generative AI and engineering to bring the best product market fit across the cross section of our user base. This deep understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers.

GrabFin's data science team is stationed across Bangalore and Singapore. We aim to hire a Data Scientist to join our Bangalore office to augment the existing Bangalore team. The data scientist will work in a relatively flat team structure with an independent mandate to build and manage critical data science models on a day to day basis. The candidate can expect to solve hard technical problems and grow into an expert on batch, real time, and LLM-driven Data Science use cases. The right candidate will have passion for technology and data science along with being a natural problem solver. This role is based out of Grab's Bangalore office.

 

The Role:

• Develop a deep understanding of Payments architecture and its nuances across use cases and countries to build predictive models for payment method recommendations, downtime management, intelligent transaction retry, payments processor selection and other such solutions to optimize payments transactions and reduce failure rates.
• Leverage advanced LLMs to power the next generation of payment experiences.
• Manage and own the entire end-to-end lifecycle of predictive models and AI agents, from development to deployment and optimization.
• Interface with engineering, compliance & operation teams to formulate solutions & product changes informed by your findings and business inputs.
• Stay current with the latest AI/LLM research and emerging frameworks and incorporate them into practical applications.
• Work independently or in a team to solve complex problem statements.
• Individual contributor role with 2+ years of experience expected.

The day-to-day activities:

• Predictive Modeling: Build predictive models using machine learning to solve for classification, ranking and online learning. Engineer features from internal data assets to build refined transaction and customer profiles.
• Generative AI Development: Design and deploy Generative AI solutions using prompt engineering, agent orchestration, and model fine-tuning (e.g., LoRA, PEFT). Build evaluation datasets and define guardrails for ongoing evaluation and monitoring.
• MLOps & Automation: Build end-to-end MLOps pipelines to automate model training, deployment, and monitoring. Track production performance and implement feedback loops for continuous improvement.
• Ownership and Collaboration: Design AI solutions by working backwards from business needs. Own the end-to-end delivery of AI capabilities, from concept through production deployment.

Qualifications

The Must Haves:

• Core ML: Expert proficiency in Python, Spark, and SQL (Presto/Hive) with a strong command of fundamental ML concepts (Bagging, Boosting, Online Learning, Recommendation Engines).
• Generative AI & Agent Frameworks: Hands-on experience with Agentic frameworks (specifically LangGraph, LangSmith, or LangChain) and LLM orchestration.
• MLOps & Productionization: Expertise in productionizing ML solutions with MLOps tools (MLflow, Kubeflow, TFX, SageMaker) and deploying scalable components on cloud platforms.
• Real-Time Streaming: Experience in the real-time implementation of machine learning solutions using Flink SQL and Flink SDK is a good to have

Engineering Excellence: Strong adherence to clean coding, modular design, and version control (Git/GitHub), with the ability to balance model performance with business trade-offs (latency, cost, scalability).

Additional Information

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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