Data Scientist - Ads and Demand Optimization

Job Description

Get to Know the Team

Join our Demand and Personalization Data Science team, where machine learning, economics, and large-scale engineering intersect. We build the core ranking, recommendation, and algorithmic incentive systems that determine what millions of users see and which merchant offers they receive across Southeast Asia. Our work directly drives discovery, engagement, and platform marketplace efficiency at scale, operating within high-throughput, low-latency production environments.

Get to Know the Role

We are looking for a Data Scientist to develop, deploy, and operate production-grade ranking and recommendation models. Reporting to the Data Science Manager II, this is a full-time 24 months contract role based onsite at the Grab One-North Singapore office. You'll collaborate with senior data scientists, product managers, and software engineers to own models end-to-end—from feature engineering and offline experimentation to live deployment and monitoring. If you're passionate about solving high-stakes marketplace algorithms at consumer scale, we invite you to apply.

The Critical Tasks You Will Perform

• Design, optimize, and maintain training-data and feature extraction pipelines across regional markets, ensuring data integrity and system reliability (including participating in team on-call rotations).
• Formulate, engineer, and validate new user and merchant personalization signals to measurably improve discovery relevance, CTR, and conversion.
• Formulate testable algorithmic hypotheses, run online A/B experiments, and monitor long-term holdout groups to rigorously measure business and user impact.
• Collaborate with Engineering to design, deploy, and scale real-time recommendation services and automated incentive allocation systems under strict SLA and latency budgets.
• Manage production ML operations, including automated retraining pipelines, feature backfills, telemetry, and proactive drift monitoring.
• Leverage Generative AI (GenAI) coding tools and AI-assisted workflows to accelerate model prototyping, automate repetitive data scripts, and drive team innovation.

Qualifications

What Essential Skills You Will Need

• At least 1 year of hands-on industry experience as a Data Scientist or Machine Learning Engineer focusing on ranking, recommendation systems, or search (or an advanced degree in Computer Science, Statistics, Operations Research, or a related field with relevant production internship experience).
• Demonstrated experience with learning-to-rank algorithms, CTR/CVR prediction, relevance modelling, or two-tower retrieval architectures (e.g., GBDT, deep ranking models).
• Experience with offline ranking evaluation metrics (e.g., NDCG, MRR, AUC, MAP) alongside practical experience designing, analyzing, and interpreting online A/B tests.
• Programming proficiency in Python and SQL, with at least 1 year of practical experience building and debugging production pipelines using Apache Spark and Airflow.
• Practical understanding of deploying ML models into real-world production environments, handling latency tradeoffs, and monitoring pipeline health.
• Experience engaging with AI tools and emerging technologies to enhance productivity, improve workflows, and contribute new ideas.

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.
• Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

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.