Senior Data Scientist (GrabFin)

Grab; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Life Insurance

GrabFlex benefits

Parental and Birthday leave

LASA volunteering leave

Grabber Assistance Programme

Job summary

Grab is seeking a data science professional to build production-grade ML systems for its Financial Services Lending products in Singapore. You will deploy predictive models, create data pipelines, and collaborate with product managers, engineers, and fellow data scientists to translate business needs into ML solutions.

You’ll report to the Principal Data Scientist, work on batch and real-time data science applications, and contribute to model refresh cycles and strategic decisions.

Qualifications

• 4+ years of experience building ML models in production environments.
• Proficient in Python and ML/DL libraries (scikit-learn, XGBoost, TensorFlow or PyTorch).
• Experience with distributed data processing (Spark, SQL).
• Experience with feature engineering and model evaluation metrics.
• Experience with multi-agent systems using LangGraph, CrewAI, or ADK.
• Ability to explain model behaviour to non-technical stakeholders.
• Experience with AI tools to enhance productivity and workflows.

Responsibilities

• Design, build, and deploy agentic systems and GenAI workflows.
• Develop scalable ML models using Python, Spark, and cloud-native tools.
• Create data pipelines and feature stores for model training and inference.
• Engineer predictive features from internal data and external sources.
• Validate model performance on real-world data and manage refresh cycles.
• Present findings to senior leadership and translate insights into policy or pricing actions.

Skills

ML production

Python programming

ML/DL libraries

Spark

SQL

Feature engineering

Multi-agent frameworks

Explainability to stakeholders

AI tools adoption

Tools

Spark

SQL

Python

LangGraph

CrewAI

ADK

Job 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.

Company Description

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

Financial Services (FS) brings together FinTech and Banking businesses across 6 countries in Southeast Asia, covering Lending, Payments, and Insurance. You will join a team building innovative financial services for drivers, consumers, and merchants within the Grab ecosystem. The team combines market insights with data science and engineering to develop products that fit real user needs. You will work in a flat structure with ownership over your models and solutions, focusing on both batch and real-time data science applications.

Get to Know the Team

Financial Services (FS) brings together FinTech and Banking businesses across 6 countries in Southeast Asia, covering Lending, Payments, and Insurance. You will join a team building innovative financial services for drivers, consumers, and merchants within the Grab ecosystem. The team combines market insights with data science and engineering to develop products that fit real user needs. You will work in a flat structure with ownership over your models and solutions, focusing on both batch and real-time data science applications.

Get to Know the Role

You will build and deploy production‑grade machine learning systems for FS Lending products serving drivers, passengers, and merchants. You will develop predictive models using machine learning and deep learning techniques, create data pipelines, and validate model performance on real‑world datasets. You will work with product managers, engineers, and data scientists to translate business requirements into ML solutions. You'll report into the Principal Data Scientist and work onsite in Grab's One North Singapore office.

The Critical Tasks You Will Perform

• You will design, build, and deploy agentic systems and GenAI workflows (using frameworks like LangGraph or CrewAI) to solve complex decision‑making problems alongside core predictive ML models, enhancing overall engineering productivity.
• You will build and deploy scalable ML models using Python, Spark, and cloud‑native tools to predict lending outcomes and customer behaviour.
• You will develop data pipelines and feature stores to support model training and inference, ensuring data flows correctly from source to production.
• You will engineer predictive features from internal data assets and identify external data sources to incorporate into model development.
• You will validate model performance on real‑world datasets and lead model refresh cycles when you detect performance drifts or gaps.
• You will present model findings to senior leadership, explaining risk trade‑offs and translating insights into strategic recommendations for policy changes, pricing adjustments, or customer targeting strategies.

Qualifications

What Essential Skills You Will Need

• At least 4 years of experience building ML models in production environments — You will deploy models that directly impact lending decisions, requiring the ability to move models from experimentation to production.
• You are proficient in Python programming and ML/DL libraries (scikit‑learn, XGBoost, TensorFlow or PyTorch) — You will write and maintain code for model development, pipeline automation, and deployment, and select appropriate algorithms for credit risk modeling and customer prediction tasks.
• Experience with distributed data processing (Spark, SQL) — You will build pipelines handling large‑scale financial data across multiple markets, requiring the ability to process data across distributed systems.
• You have experience with feature engineering and model evaluation metrics — You will create features from raw transaction and behavioural data, and select metrics that measure model performance for financial applications.
• You have experience with multi‑agent systems using frameworks like LangGraph, CrewAI, or ADK — You will implement agent‑based systems for complex decision‑making workflows using patterns such as ReAct, self‑reflection, or hierarchical delegation.
• You can explain model behaviour to non‑technical stakeholders — You will present to product managers and leadership, requiring you to communicate technical concepts in accessible language and connect model outputs to business outcomes.
• You have experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.

Additional Information

Life at Grab

• 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.