Data Science Research Intern

This internship supports research and analysis using real-world food, health, and lifestyle data. The intern may form hypotheses, conduct analyses, and consider whether the results can influence people’s behavior.

Typical projects include designing and evaluating recommendation systems using ingredient, recipe, menu, and nutrition data; analyzing and visualizing clinical research data with university hospitals; and analyzing dietary tendencies and activity logs to prepare reports for business projects. The work draws on data from the company’s consumer meal-management app, the Kakaris meal-guidance system for medical institutions, and joint projects with pharmaceutical, food, and insurance companies.

The available data includes records from several hundred thousand users, including weight, sleep, and meal information, more than 10,000 recipes, and over 2 million menu records. The research and development team works across statistical analysis, machine learning, visualization, and recommendation systems. It consists of three full-time members and three student part-time members, with collaboration across engineers, registered dietitians, designers, and sales staff. Team communication and regular reviews use Slack and Notion.

Required experience includes preprocessing and aggregation with Python and data extraction with SQL. Knowledge of web services using Ruby on Rails, interest in machine learning or visualization tools, and interest in food, healthcare, papers, or research are welcomed.

Operational logs stored in BigQuery are used for aggregation, analysis, and preprocessing with Python and SQL. Notion and Google Slides are used for team sharing and reporting. Depending on the intern’s preference, the role may also include Python implementation and visualization. The position is an internship based in Tokyo, and online interviews are available. The posting does not state a salary, schedule, internship duration, benefits, or visa sponsorship.