Senior Data Scientist (GrabFin)

GrabTaxi Holdings Pte. Ltd.; Singapore; On-site; SGD 70,000 - 100,000; Full time

Benefits offered by this job

Term Life Insurance

Medical Insurance

Flexible benefits package

Parental leave

Birthday leave

Volunteering leave

Grabber Assistance Programme

Job summary

GrabTaxi Holdings Pte. Ltd. in Singapore seeks an experienced Machine Learning Engineer to build and deploy production-grade ML systems for FS Lending products. You will work closely with product managers and engineers to translate business requirements into effective ML solutions.

The ideal candidate has at least 3 years of experience, strong Python skills, and the ability to communicate technical concepts to non-technical stakeholders. The role offers a comprehensive benefits package including insurance and flexible working arrangements.

Qualifications

• At least 3 years of experience building ML models in production environments.
• Experience with multi-agent systems using frameworks like LangGraph or CrewAI.
• Proficiency with ML/DL libraries (scikit-learn, XGBoost, TensorFlow or PyTorch).
• Experience with feature engineering and model evaluation metrics.
• Ability to explain model behavior to non-technical stakeholders.

Responsibilities

• Build and deploy scalable ML models using Python and cloud-native tools.
• Develop data pipelines and feature stores for model training and inference.
• Validate model performance on real-world datasets and lead refresh cycles.
• Present model findings to senior leadership and make strategic recommendations.

Skills

Machine Learning models

Python programming

Distributed data processing (Spark, SQL)

Feature engineering

Model evaluation metrics

Communication with non-technical stakeholders

Experience with ML/DL libraries (scikit-learn, TensorFlow)

Multi-agent systems

Job description

Get to Know the Role

You’ll build and deploy production‑grade machine learning systems for FS Lending products serving drivers, passengers, and merchants. You’ll develop predictive models using machine learning and deep learning techniques, create data pipelines, and validate model performance on real‑world datasets. You’ll 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 One North Singapore office.

The Critical Tasks You Will Perform

You will:

• Build and deploy scalable ML models using Python, Spark, and cloud‑native tools to predict lending outcomes and customer behaviour.
• Develop data pipelines and feature stores to support model training and inference, ensuring data flows correctly from source to production.
• Engineer predictive features from internal data assets and identify external data sources to incorporate into model development.
• Validate model performance on real‑world datasets and lead model refresh cycles when you detect performance drifts or gaps.
• Present model findings to senior leadership, explaining risk trade‑offs and quantifying business impact in clear terms.
• Translate model insights into strategic recommendations for policy changes, pricing adjustments, or customer targeting strategies.

What Essential Skills You will Need

• At least 3 years of experience building ML models in production environments — You'll deploy models that directly impact lending decisions, requiring ability to move models from experimentation to production.
• Experience with multi‑agent systems using frameworks like LangGraph, CrewAI, or ADK — You'll implement agent‑based systems for complex decision‑making workflows using patterns such as ReAct, self‑reflection, or hierarchical delegation.
• Python programming for ML development — You'll write and maintain code for model development, pipeline automation, and deployment. You can demonstrate this through prior work on ML systems.
• Experience with distributed data processing (Spark, SQL) — You'll build pipelines handling large‑scale financial data across multiple markets, requiring ability to process data across distributed systems.
• Proficiency with ML/DL libraries (scikit‑learn, XGBoost, TensorFlow or PyTorch) — You'll select and apply appropriate algorithms for credit risk modelling and customer prediction tasks.
• Experience with feature engineering and model evaluation metrics — You'll create features from raw transaction and behavioral data, and select metrics that properly measure model performance for financial applications.
• You can explain model behavior to non‑technical stakeholders — You'll regularly present to product managers and leadership, requiring you to communicate technical concepts in accessible language and connect model outputs to business outcomes.

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.

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.