If you want to directly shape future products and technologies, then this is your opportunity! Advantest is one of the world’s leading providers of automatic test equipment for the semiconductor industry. We work closely together with leading companies in the most exciting, emerging markets to enable future technologies. Almost any modern smartphone, cloud system or automobile is relying on semiconductors that have been tested with our products.
We strive for continuous improvement, especially in the areas of SW quality, performance, and reliability. Our core SW product is SmarTest - a large software system consisting of several million lines of C++/ Java code. More than 100.000 automated test cases are continuously executed, which results in a huge amount of test related data and metadata.
We are looking for a Data Science / ML Engineer (m/f/d), who implements and optimizes the full data processing and analytics pipeline to enable continuous learning and improvement based on insights gained from our existing data sets. With that you directly support improving existing testing strategies and executions and help to develop new approaches to maintain the lead of SmarTest as the best ATE-software for our customers.
In the role of a Data Science / ML Engineer (m/f/d) you will:
- Join a team of experienced SW engineers and test experts who aim towards the common goal of improving the efficiency, effectiveness, and flexibility of our test process
- Establish and grow the application of data science and machine learning in SW-test at Advantest
- Build the foundation for a data processing and analytics solution, that can handle several millions of data points daily - develop the concept and evaluate, implement, and continuously improve the solution
- Understand existing data set, choose & identify appropriate features, retrieve, and process the data, derive insights and learning - in close cooperation with the SW development and system testing teams
- Take over and further optimize the existing business KPI monitoring solution – identify and implement synergies with the overall data processing and analytics architecture
- Choose and adapt data analytics and machine learning algorithms and models
- Closely interact with internal data science departments to algin initiatives and identify learnings and synergies
- Technical lead of a team of data scientists and machine learning engineers located at a partner company
- Collaborate with the R&D teams in Germany, US, China, and Japan to find solutions for the most pressing needs in SW-test
