Analyze JMDC and Omron Group data to develop new data-driven services, build predictive models, advise industry clients, improve services with machine learning, and publish findings.
About this role
The MLOps Engineer uses machine learning on JMDC's healthcare data to create new value. The role includes data-analysis consulting for insurance companies and healthcare businesses, building predictive models, providing services, and improving the value of services operated by business units and group companies.
The engineer is expected to advance projects independently and autonomously, from problem definition through social implementation. The position provides experience in developing and operating services using data science and machine learning, analyzing a large healthcare database, and applying statistical and machine-learning skills. Healthcare and medical-domain knowledge can also be developed through the work.
Required qualifications include logical thinking, experience working in a team according to a Git branching strategy such as Git Flow or GitHub Flow, and experience designing, developing, and operating externally facing API services while considering non-functional requirements. Experience designing, developing, and operating systems using PaaS or FaaS is required. The role also requires experience applying infrastructure as code and CI/CD based on DevOps principles, including log collection and performance monitoring.
Preferred experience includes delivering and continuously improving production services using MLOps, implementing machine-learning models or methods proposed in recent papers, placing in data-analysis competitions such as Kaggle, developing healthcare-focused data-science or machine-learning models, and having specialist biostatistics or clinical knowledge for medical research. The role also seeks strong oral and written communication, an interest in new things, and a commitment to self-development.
The technologies include Python and SQL; Amazon SageMaker, AWS Fargate on ECS, AWS Lambda, AWS Athena, Amazon Redshift Serverless, Amazon DynamoDB and Vertica; Terraform; GitHub Actions and AWS CodeBuild; and tools including Gemini Advanced, NotebookLM, ChatGPT Plus, GitHub Copilot, Slack, Backlog, Confluence, Google Workspace and GitHub Enterprise. Windows notebook and computing desktop equipment or a MacBook Pro is provided.
The work location is the Tokyo office in Minato, Tokyo.
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