Data Scientist (GATD)

Job Description:

Rakuten Group, Inc. is a global leader in internet services and has a diverse ecosystem spanning across e-commerce, fintech, communications and more serving approximately 1.8 billion members worldwide. Founded in Tokyo in 1997, the Group operates in over 30 countries and regions with more than 30,000 employees.

Based in Singapore's Central Business District, Rakuten Asia Pte. Ltd. serves as the regional headquarters for Asia, driving value through areas such as advertising product development, product strategy, and data management to support Rakuten Group's global ecosystem.

Learn more at: https://global.rakuten.com/corp/

The Global Ad Technology Department (GATD) manages the whole of the advertising systems that power Rakuten. We are a cross-functional and data-driven organization working together in a diverse team spread across five countries: Japan, Singapore, India, China and UK.

GATD Website:

Our vision is to empower our internal and external stakeholders by providing data driven marketing solutions by developing the Ad delivery, Audience Management, Tracking, Reporting and Data Sync Platforms. Joining us, you will be able to challenge yourself in a wide range of technologies in the frontline of heavy traffic large scale ad applications and platforms, including high performance system development and big data processing systems. Also, you will be able to work about latest digital advertising and Ad platform because we also closely work with outside Ad platformer as well.

In the platform team, we have positions who have comprehensive knowledge of the platforms and provide total solution for business requirement by combining of multiple platform components.

Our team develops and operates an ad serving platform that is widely used in Rakuten's overall services, including Rakuten Ichiba. The system consists of servers that respond to high traffic, such as tens of thousands of QPS, with low latency of less than 100ms, a backend system that processes huge log data of tens of billions of data per month, and campaign management UI.

With the practical adoption of AI, decision-making in ad serving is becoming faster and more sophisticated, and competition among platforms is intensifying. In this context, our ad serving platform (RUNA) is in a phase of differentiating itself by strengthening the in-house development of core algorithms centered on price optimization, ad performance maximization, and creative optimization. In addition, RUNA’s adoption within the Rakuten Group continues to, and as the scale of delivery and the diversity of use cases grow, we need to enhance model generalization, experiment velocity (A/B testing), and operational reliability. To address these external changes and rising internal demand, we are seeking data scientists who can drive initiatives end to end—from hypothesis formulation and modeling to online deployment, evaluation, and continuous improvement.

Responsibilities:

Problem definition for ad delivery optimization and the design of KPIs/metrics, along with observability (dashboards and alerts).

Data preprocessing, feature engineering, modeling, and offline evaluation (including simulation) for price optimization, CTR/CVR and value prediction, and creative optimization.

Online deployment and experiment design: A/B tests/bandits, calibration, rollout strategy planning, effectiveness evaluation, and continuous improvement.

Production operations and MLOps: building training/inference pipelines; monitoring and drift detection; model updates and automated rollback; quality and privacy governance.

Collaboration with internal stakeholders (product, engineering, sales/operations) on requirements definition, decision support, documentation, and knowledge sharing.

Work Environment

Development team

About 20 people (SRE, Backend/Frontend, Data, SDK, QA)

Development Environment

Google Cloud Platform(GKE, Dataflow, Cloud Pub/Sub, BigQuery, Cloud SQL)

Aerospike

Terraform

Ansible

Python

Go

Related systems, advertising products

Ad Platform / DMP / Data feed / Tracking and reporting / Pixel tag

Listing ads, Display ads, Video ads, and Google shopping ads

Requirements:

3+ years of hands-on experience in data analysis and machine learning using Python and SQL; proficiency with Pandas/NumPy/scikit-learn and data visualization tools

Experience processing large-scale data (e.g., Spark, BigQuery) and building reproducible analytics environments (using notebooks and repositories together, code reviews, testing)

Solid foundation in statistics, probability, causal inference, and experimental design (hypothesis testing, sampling, A/B test design and analysis, effect size estimation)

Experience developing machine learning models (regression, classification; tree-based methods/GBDT/logistic regression/simple neural networks) with rigorous evaluation design (offline/online metrics, calibration)

Foundational knowledge of online/digital advertising (CTR/CVR prediction, bidding and budget pacing, ad serving control, KPI optimization) or practical optimization experience in adjacent domains

Feature engineering oriented toward price and serving optimization use cases; data quality management, leakage prevention, and handling delayed/late-arriving labels

Production experience (model deployment, scheduling/pipeline operations, monitoring, implementing and operating drift detection)

Communication skills for collaborating with stakeholders on requirements definition, analysis design, and decision support (including explaining and visualizing deliverables)

Degree in computer science, information engineering, statistics, applied mathematics, or a related field; or equivalent practical experience