Data Scientist
micware, celebrates its 20th anniversary in March 2023 as an in-vehicle software company. Starting with the development of car audio and other vehicle systems, the company began developing car navigation systems in 2009. Currently, the system is installed in more than 600,000 units per year by major automakers. In the MaaS market, which is expected to be worth 900 trillion yen worldwide by 2050, we have set the following goals: - Seamless mobility proposals - 3D maps connecting the past and the future - Recommendations and future forecast information to users Our business is growing steadily and we are planning to develop new services. We are looking for a data scientist who will contribute to service growth by utilizing data as a member of a group of professionals who have mastered "mobility"! Responsibilities: - Analysis and logic development of data collected from IoT devices - Analysis of data collected from IoT devices and logic development utilizing the results, such as the following - Mobility (logistics) - Energy (electricity) - Environmental data (temperature, humidity, CO2 concentration) This is a challenging project as an engineer because you will be able to listen to customer opinions and reflect the proposals and improvements of new functions in your own services! Details will be provided in the interview. First, let's talk casually!
- Clear evaluation system Skills are visualized in terms of scores, and salaries and bonuses are determined based on individual skills rather than seniority. The attractive point is that we have established a system that rewards employees for their efforts. - Stimulating growth market In the automotive industry, which is undergoing a major revolution, you will be involved in the development of new experiences for users and the creation of the future of mobility, while making use of our accumulated in-house knowledge.
- Data analysis skills - Machine learning *Basically, any method is acceptable.
- Use of data analysis tools such as Pandas, Numpy or R - Use of machine learning tools such as scikit-learn
- Those who find it rewarding to develop and provide their own products and services. - Those who are able to propose and execute new methodologies on their own, rather than just using the current development environment and systems.