Job Responsibilities

• Lead Ad-Tech optimization initiatives using ML to improve campaign outcomes.
• Identify business challenges, design evaluation plans, and build/iterate ML models.
• Prioritize mid-to-long-term impact and propose key improvements.
• Develop ML models for ads (recommendation, matching, classification) and apply statistics to derive insights.
• Use embeddings for images/text and design time-series models to evaluate ad effectiveness and budgets.
• Lead end-to-end ML product lifecycle; address scale (20M+ MAUs); balance accuracy with UX.

Technical Stack

Mandatory Skills

• SQL, Python, Go
• Fundamentals of ML; experience with scikit-learn and LightGBM
• Basic to intermediate statistics; data-analysis-to-output workflow
• Digital marketing knowledge; Ad-Tech optimization experience

Nice-to-have Skills

• Kubernetes-based microservices
• Large-scale ETL/ELT pipelines
• Advertising recommendation models
• Large-scale search systems
• Language: Japanese native or English B2 (bilingual capability)

Career Growth Perspective

• Exposure to a high-scale Ad-Tech ML platform with 20M+ MAUs, delivering measurable business impact.
• Opportunity to own end-to-end ML products—from planning to deployment—enhancing leadership and cross-functional skills.