Data Science Engineer in Japan
Employer Type : Recruiter / Dispatch / Temp Agency
Industry : Information Technology, Internet
Salary : 6 million yen ~ 10 million yen JPY Year
English Level : Business Level
Japanese Level : Basic Level
Restricted to Domestic Applicants? : Japan only
Visa Sponsorship – Yes
【About the company …】
【”Unleashing the potential of the manufacturing industry” through technology】
In the manufacturing industry, which is said to be worth 180 trillion yen in Japan, many manufacturers and their supply partners have been constrained by a variety of reasons, including being too busy with quotation and management tasks, lacking sales capabilities, and lacking information and networks, and are unable to fully utilize their original development and technological capabilities.
The company’s mission is to unleash the potential of each company by resolving these constraints from various aspects.
In order to achieve this goal, we need to utilize technology mainly in areas that have not yet been digitized, so that all manufacturing companies, whether they are small town factories, large-scale manufacturers with a long history, or start-up companies just starting out, can utilize their strengths to shine and create a lot of new value. Why don’t you use your technology to achieve such a future?
【”Unleashing the Potential of the Manufacturing Industry” with Data Science】
In the manufacturing industry, there are still many tasks that are done manually. Tasks that require human judgment, such as reading drawings and estimating manufacturing costs, have been difficult to automate. However, the company has a lot of data generated in the process of ordering and manufacturing processes. The company believes that trying to create some kind of pattern for this data will lead to the improvement of the entire process of the manufacturing industry.
In addition, there must be a lot of other data in the manufacturing industry that has yet to be fully utilized. The reform of the manufacturing industry itself will surely start by making it easier to utilize various data through data science.
Example 1: Drawing Analysis
・Analyze the drawings of the company’s partners and develop the technology to extract the information on the drawings.
– Automatic information extraction from drawings
– High resolution processing of drawings
– Search for similar drawings
– Automatic process decomposition from drawings
Example 2: Supply Chain Data Analysis
After receiving an order from the client, the company builds and manages a very long supply chain, including the selection of supply partners, production management, and acceptance at distribution bases. Analyzing data in the supply chain to reduce costs and improve economics for the future has become a major theme. They formulate hypotheses to implement them, verify the hypotheses through data analysis, and perform the actual data analysis work.
– Establish issues and build hypotheses through observation of the company’s operations and discussions with stakeholders.
– Lead the development of data collection and analysis infrastructure in collaboration with other internal teams and client companies
– Development of data analysis and optimization methods for demand forecasting, inventory optimization, etc.
– Languages used: Python, R
– Frameworks and Libraries: TensorFlow, PyTorch, scikit-learn
– Development tools: GitHub, CircleCI, Jupyter Notebook, Google Colab
– Communication tools: Slack, Discord, JIRA
– Automatic design error detection from drawings
– Drawing analysis team of several people
– Team members with diverse skill sets, including CAD data veterans and former ML researchers
– Manufacturing costing team of several people
– Development by competitive programming experts and backend engineers, mainly using Rust
– Scrum-based development cycle
– Ticket management by JIRA
＜A point of bold challenge and excellence＞
The company is currently working in the area of “high-mix low-volume production procurement” in the manufacturing industry. Because this is an area where little innovation has occurred to date, there are many problems for which there are no precedents or solutions, and solving them with algorithms is interesting because it is an unexplored area.
In addition, the company wants to not only utilize the data that is currently accumulated, but also to think about what kind of innovation can be brought about with what kind of data. Why don’t you use your skills to take on the challenge of bringing about change through the accumulation of data?
– Empathy for unleashing the potential of the manufacturing industry
– Basic knowledge of statistics
– Research or practical experience using machine learning
– Experience in Python development
– Ability to solve problems based on real data, especially to define appropriate tasks that satisfy customers and are technically solvable
– Experience using version control systems such as Git
– Experience in development using GPU processing
– Experience participating in and winning data analysis competitions such as Kaggle
– Ability to research and read the latest papers and create survey materials
– Experience developing with Rust
– Expertise and experience in mathematical optimization (continuous optimization, discrete optimization, combinatorial optimization, etc.)
– Experience in data processing using SQL
– Experience in designing, building, and operating an overall data processing process
– Data handling in a cloud environment such as GCP
【 Working time 】
・Commuting allowance (up to 30,000 yen)
・Vacation (summer vacation, year-end and New Year’s vacation, refreshment vacation, bereavement vacation, etc.)
・Subsidies (moving subsidies, child allowances, marriage congratulation money, etc.)
・Office convenience store
・Learning support (book purchase system, language learning support, manufacturing experience, external training support, etc.)
・Engineers can apply for a PC and display with their desired specifications.
※The maximum amount is 400,000 yen, within which you can also purchase accessories for the PC.
※The PC replacement cycle should be at least two years.
【 Holiday 】
・Full holiday 2 day system (Saturday / Sunday) holidays
・New Year holidays
・Annual paid leave