This role sits within Money Forward’s company-wide AI & data strategy organization (CDAO Office). In the Financier domain in particular (financial services / credit), you will lead the technical strategy and execution of an ML platform.
You will be responsible for end-to-end technical decision-making for designing a secure and efficient foundation to leverage large-scale financial transaction data, and for the technical direction of product implementation.
Background
To advance decision-making using Money Forward’s vast financial data (e.g., credit assessment), the platform side is held to an extremely high bar:
- Large-scale transaction processing: Build data pipelines that can process data at the scale of tens of millions of users without loss and with low latency, and supply it to products.
- Financial-grade governance and security: Build an architecture that ensures explainability and auditability at the code level, aligned with the Financial Services Agency’s model risk management principles and international AI ethics principles.
- Company-wide technical standardization: Define a reusable, cross-company MLOps environment while meeting product-specific requirements, and make technology choices that maximize development efficiency.
Technology Stack
- Platform: AWS (SageMaker, Lambda, ECS, S3, etc.), Databricks
- Data: Python (FastAPI, etc.), SQL, Apache Airflow / Step Functions
- DevOps: Terraform, GitHub Actions, CodePipeline
- Communication: Slack, Notion
Responsibilities
- Define the ML platform technical strategy and roadmap
- Translate business requirements into technical specifications and decide medium-to-long-term architectural direction.
- Design and oversee large-scale data engineering
- Design data pipelines for high-traffic environments using Databricks and AWS, with performance considerations.
- Define implementation policies for governance and security
- Establish “Security by Design,” including IAM/permission design, and build a foundation that balances security with operational ease.
- Drive technical alignment with stakeholders
- Coordinate and prioritize with Engineering, Legal, Compliance, and Business teams based on technical validity.
Requirements
- Software engineering experience (approx. 5+ years)
- Design, development, and operations experience in backend, infrastructure, and/or data platforms.
- Technical leadership experience
- Experience taking responsibility for architecture selection and technical decision-making as a tech lead or PM.
- Data engineering expertise
- Proven results building large-scale datasets (ETL/DWH/data lakes) and performance tuning.
- Strong documentation skills
- Ability to clearly articulate complex technical specifications and design rationale for stakeholders.
- Business level Japanese (equivalent to JLPT N2 or above)
- Basic business level English (equivalent to TOEIC 700 or above)
Nice to haves
While not specifically required, tell us if you have any of the following.
- Hands-on MLOps experience
- Building deployment/operation flows using Amazon SageMaker and/or Databricks.
- Financial domain knowledge
- Experience building systems aligned with credit/risk measurement and FISC security guidelines.
- Product management track record
- Roadmap management that maximizes product value within technical constraints.
Compensation
¥7,500,000 ~ ¥12,000,000 annually.
