MLOps / Lead Data Pipeline Engineer

About the Role

We are searching for a hands-on MLOps / Data Engineering Specialist who can bridge the gap between experimental data science models and stable, high-reliability production systems in the credit and risk domain.

What We Are Looking For

• Deep Data & ML Pipeline Expertise: Proven track record of designing, building, and operating production-grade data pipelines that feed machine learning models smoothly.
• Credit & Risk Assessment Fit: Ability to handle complex financial/credit data structures (credit scoring, risk evaluation, debt collection models) with strict accuracy and high availability.
• Production Stability: Capability to take models generated by internal Data Scientists and build automated, reliable operational systems around them.

What You’ll Do

• Architect Data & ML Pipelines: Build and maintain scalable data ingestion and feature processing pipelines on cloud environments (GCP BigQuery).
• Production Deployment: Productionize ML models (credit scoring, screening logic) using automated MLOps framework tools (Vertex AI, SageMaker, or DataRobot).
• Cross-Team Collaboration: Partner directly with internal Data Scientists and business stakeholders to operationalize insights into direct business value.
• Monitoring & Automation: Implement model drift monitoring, data quality checks, and automated retraining workflows.

Required Qualifications

• Language: Fluent to Native-level Japanese (essential for cross-functional alignment and business communication).
• Experience: 3+ years in Data Engineering, MLOps, or ML Pipeline development.
• Technical Stack: Strong proficiency in Python, SQL, and Cloud Data Warehouses (GCP / BigQuery or AWS).
• Domain Mindset: Background or strong interest in financial data, credit assessment, payments, or risk screening systems.

Perks & Working Culture

• Fully flexible schedule with no core time.
• Hybrid Work

How to Apply

If you have strong data pipeline engineering experience and want to solve key infrastructure challenges for a major payment ecosystem, click Apply below.