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Company Name
MI-6 Co., Ltd.
Job Type
[DS] Data Scientist
Work Detail
You will be responsible for project leadership, developing and proposing solutions to accelerate research and development using AI and informatics. [About MI-6] MI-6 aims to be an R&D platform company that promotes R&D DX in the chemical and materials industries. Its flagship product, the R&D platform "miHub®," is continuously used in research sites of major materials manufacturers and manufacturing companies. It serves as a foundation supporting data-driven R&D, from managing and sharing research data to supporting materials discovery. Currently, we are transitioning from the phase of expanding adoption to a phase of deepening its use in research operations. We are also working on hands-on support by data scientists highly knowledgeable in MI, and enhancing experimental processes through Lab Automation. We are building a platform that integrates data infrastructure, informatics, simulation, and experimental environments to realize a digital twin of the R&D process. The materials industry is a massive industry, worth approximately 550 trillion yen globally and approximately 100 trillion yen in Japan, but R&D DX is still in its early stages. MI-6 is promoting the development and dissemination of a new R&D platform in this area. 【Mission】 MI-6's mission is to evolve the research and development process through the social implementation of "materials informatics." Research and development in the materials and chemical industries still heavily rely on individual tacit knowledge, and a research foundation where knowledge, data, theory, and context are systematically linked is not yet fully established. We are working to build a research environment where digital and physical processes circulate by utilizing AI and robotics to connect data accumulation and analysis with experimental processes. We realize a development process where exploration, verification, and learning are continuous, increasing the speed and reproducibility of materials discovery and process development. We will support the advancement of research and development in the materials and manufacturing industries in Japan and around the world, and contribute to the creation of next-generation materials technologies. ■About the Position This is a candidate position for leader of the data scientist team that technically supports all of MI-6's businesses. The role involves enhancing the value of professional services that deliver results hands-on (directly and collaboratively) to customers' research and development challenges from a technical perspective. In this position, you will lead a series of projects, from appropriately structuring customer challenges to designing optimal solutions using data science, building models, and delivering deliverables. You will be responsible for project leadership, developing and proposing solutions to accelerate customer R&D with AI and informatics. You will leverage your creativity to combine various technologies and create value. ■ Position Highlights You will gain knowledge in physical R&D areas such as materials development, chemical processes, and experimental measurement. Furthermore, MI-6 has experts in various fields, including software engineers, Lab Automation engineers, and machine learning researchers, allowing you to work on designing integrated solutions that cover the entire "R&D cycle." 【Job Responsibilities】 ・Structuring customer R&D challenges ・Promoting assigned projects ・Introducing new technologies and establishing standard processes ・Proposing and executing new solution plans *Regarding the Selection Process for this Position While this position is intended for full-time employment, we may ask you to undertake side work during the selection process to ensure a good match for both parties. We require at least 10 hours of work per week, but it is possible to dedicate time outside of your main job hours or on weekends, so you can work on this while continuing your current job. Compensation for the part-time work will be paid according to the hours worked. [Expected Selection Process] Document Screening → Multiple Interviews (approximately 2-3 times) → Reference Check & Background Check → Final Interview
Ideal Profile
Required Skills • Practical experience in data analysis • Experience in machine learning or statistical modeling • Ability to structure customer challenges and translate them into technical solutions • Ability to clearly communicate technical content through slide creation and written documentation • Experience in task management and project progress Preferred Skills • Technical knowledge related to the MI (Materials Informatics) domain • Basic understanding of materials, chemistry, and manufacturing processes • Experience using data infrastructure and visualization tools • Building highly reproducible analysis environments using Python • Experience in explaining technical details to customers, creating reports, and making proposals Desired Candidate Profile • Someone who is sincere in addressing customer R&D challenges and takes responsibility for the results • Someone who can balance technical correctness with sound problem-solving principles • Someone who can translate analysis results into a form that researchers can actually use • Someone who has a habit of structuring things and organizing relationships • Someone who is interested in sharing knowledge within a team to improve reproducibility and quality
Work Location
Phd. Stating Salary
5 million to 9 million yen *The above amount includes deemed overtime pay for 30 hours.
Selection Flow
*Regarding the selection process for this job posting While this position is intended for full-time employment, we may ask you to take on a side job during the selection process to ensure a good match for both parties. We request at least 10 hours of work per week, but it is possible to take time off outside of your main job hours or on weekends, so you can continue working at your current job. Compensation will be paid according to the hours worked during the side job period. [Expected Selection Process] Document screening →Multiple interviews (approximately 2-3 times) →Reference check and background check →Final interview