Data Scientist -RC

Career Opportunity for a Data Scientist in Japan! 

 

■ Data Scientist

 

■ Company Overview

An e-commerce, fintech, digital content and communications company with more than 30,000 employees, and operations in 30 countries and regions.

 

■ Your Role and Responsibilities 

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 Platforms. 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.

Position Detail

●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.

 

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

 

 

■ Experience and Qualifications

●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

●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)

 

■ Additional Preferred Qualifications
●Knowledge of ad auctions and mechanism design (first-price/second-price, bid shading, reserve price optimization, frequency control/capping)

●Hands-on experience applying price optimization methods (Bayesian optimization, multi-armed bandits, contextual bandits, reinforcement learning, etc.)

●Experience with creative optimization (multivariate testing, bandit optimization, image/text feature extraction, use of generative AI)

●Experience building serving-control models and simulations (e.g., budgeting, pacing, inventory forecasting)

●Experience implementing and operating streaming/real-time processing platforms (Kafka/Flink/Beam) and online (real-time) inference

●MLOps practices (feature stores, model registries, CI/CD, Docker/Kubernetes, monitoring/alerting, data drift/concept drift detection)

●Experience with cloud environments (GCP: BigQuery/Vertex AI/Dataflow, or equivalent services on AWS/Azure)

●Professional experience leveraging AI in real-world applications

■ Good Reasons to Join

● Hybrid position in Japan

● Work with International team members

●Language: Fluent Japanese speaker or have N2 Level of the Japanese Language Proficiency Test

 

 

■ Work Location

Tokyo, Japan

 

Details will be provided during the meeting.