Use Python and SQL to analyze real-world food, health, and lifestyle data, contributing to recommendation systems, clinical research, visualizations, and business reports in a Tokyo R&D internship.
About this role
This internship focuses on analyzing real-world data related to food and health for a service and research team. Work includes designing and validating recommendation systems using ingredients, recipes, menus, and nutritional information; designing and analyzing data for clinical research conducted with medical institutions such as university hospitals; visualizing research data; and preparing reports on eating patterns and behavioral logs for business projects. Improving recommendation logic that affects service KPIs is also one of the stated themes.
The available data includes weight, sleep, meal, and other life-log records from hundreds of thousands of users, more than 10,000 recipes, and over two million menu records. Operational logs are stored in BigQuery. The role uses Python for preprocessing, aggregation, and analysis, and SQL for data extraction. Notion and Google Slides are used for team sharing and reporting. Depending on the intern’s interests, the role may also include Python implementation and visualization.
The work is connected to the development and operation of the consumer meal-management app Oishi Kenko and the introduction and analysis of Kakaris, a meal-guidance system for medical institutions. The company conducts clinical research and publication with university hospitals and joint projects with pharmaceutical, food, and insurance companies, with more than 500 such projects stated in the posting. Applications of generative AI and large language models are also being explored.
The research and development team consists of two full-time members and five student part-time members. Its members have expertise in machine learning, statistical analysis, visualization, and recommendation systems. Analysis topics span product development, academic research, and business-to-business projects. Team members communicate through Slack and Notion and share progress and results through regular reviews.
Required experience includes using Python for preprocessing or aggregation and using SQL to extract data. Knowledge of web services built with Ruby on Rails, interest in machine learning or visualization tools, interest in food or healthcare, and interest in papers or research are welcomed.
This is an internship position in Tokyo, and online interviews are available.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Develop and improve Android apps for health and nutrition services. Analyze user behavior, define features, improve app experiences, review code, test releases, and maintain mobile CI/CD.
As a data science research and development intern, analyze real-world food, health, and lifestyle data with Python and SQL for recommendation, clinical-research, and business-reporting projects.
Develop end-to-end machine-learning models for autonomous-driving taxis from camera and LiDAR data, then evaluate and optimize them in simulation and real vehicles.
Build and operate shared AWS cloud infrastructure across multiple products, using Terraform, Kubernetes and GitHub Actions to improve reliability and incident response.
Build and manage internal IT and security foundations, including policies, security tools, Microsoft 365, assets, accounts, help desk, and workflow automation. Remote and office work are available.