Job Description

[English only / Visa support] Applied Scientist

 

 

■ Job Title

Applied Scientist

 

■ Company Overview

Japanese Space tech Venture Company

 

■ Your Role and Responsibilities 

 

You will join a team of scientists dedicated to researching, designing, and enhancing models that form the foundation of the solutions.

Details of Work

Investigate algorithms and implement code to derive meaningful insights from SAR imagery.
Identify appropriate methodologies for each challenge through literature analysis and experimentation, leveraging tools like image processing, statistical learning, deep learning, and others.
Augment your models by incorporating additional data sources, such as optical satellite imagery, infrastructure data, weather information, and more.
Collaborate closely with fellow scientists and business stakeholders to devise effective solutions for diverse needs and challenges.
Use version control systems like Git to manage software development and streamline collaboration within the team.
Contribute to the creation and refinement of visualizations for various models and solutions.
Commit to continuous learning and development for both yourself and your team.

 

■ Experience and Qualifications

Bachelor’s degree in Data Science, Statistics, Computer Science, or a related discipline.
A minimum of 2-3 years of hands-on experience with Python and its scientific libraries (e.g., NumPy, Pandas, Jupyter, etc.).
At least 2-3 years of professional experience working in a Unix-based environment and with Git for version control.
Proven experience (2-3 years) in applying statistics and machine learning techniques.
Ability to perform literature reviews and efficiently replicate methodologies from research publications.
Enthusiasm for acquiring new skills and sharing knowledge with the team.

■ Additional Preferred Qualifications

Master’s degree in Data Science, Statistics, Computer Science, or a closely related field.
Familiarity with SAR data and its application in earth observation projects.
Professional experience (2-3 years) working with machine learning and deep learning tools, such as Scikit-Learn or PyTorch.
Proficiency (2-3 years) in GIS libraries, including GDAL and Rasterio.
Strong verbal and written communication skills in English, with the ability to effectively explain analytical techniques and results to both technical and non-technical audiences.

■ Good Reasons to Join

English Environment

Expenses support for learning languages and other needed study for the job

The market is expanding

 

■ Work Location

Tokyo

 

■ Salary 

negotiable

 

 

Details will be provided during the meeting.