Data Scientist - Technical Leader (Semiconductor Equipment) at Salveinno

, , Japan -

Full Time

Start Date

Immediate

Expiry Date

31 Mar, 26

Salary

0.0

Posted On

31 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Machine Learning, Algorithm Development, Python, MATLAB, R, Software Development Lifecycle, Testing, Technical Documentation, Collaboration, Communication, Customer Interaction, Abnormal Behavior Detection, Failure Prediction, Equipment Automation, Autonomous Operation

Industry

Human Resources Services

Description

Location: Kurokawa-gun, Miyagi Prefecture, Japan Work model: On-site (customer-facing role) Domain: Semiconductor Manufacturing Equipment / Applied Machine Learning This role sits at the intersection of data science, machine learning, and semiconductor equipment engineering. As a Data Scientist - Technical Leader, you will analyze large volumes of equipment and process data, develop machine-learning–based algorithms, and integrate them directly into tools and equipment control systems. Your work will support abnormality detection, failure prediction, automation, and autonomous operation of semiconductor manufacturing equipment. The role is hands-on and applied, with strong customer interaction in a Japanese manufacturing environment. This is not a research-only or academic data science position. Responsibilities Analyze data generated by semiconductor manufacturing equipment Develop and implement machine learning and data-driven algorithms for: Abnormal behavior detection Failure prediction Equipment automation and autonomy Integrate developed algorithms into tools and equipment control systems Conduct testing within data analysis and software systems Understand and analyze customer and system requirements Coordinate between internal teams and customers to resolve technical issues Support QA testing and validation activities Deliver high-quality outputs on schedule Report progress, risks, and issues to stakeholders Build and maintain strong working relationships with Japanese customers Requirements Proven experience in algorithm development using machine learning or related techniques Strong proficiency in Python, MATLAB, or R for data analysis and algorithm development Experience working across the software development lifecycle (SDLC) Experience in software design, testing, and test case development Strong analytical thinking and technical documentation skills Experience applying data science to real-world systems, not only offline analysis Ability to translate data insights into deployable, production-ready solutions Comfortable working in manufacturing or equipment-driven environments Strong collaboration and communication skills in customer-facing environments Ability to coordinate between teams and remove blockers to execution Japanese: Native level / JLPT N2 or above English B2 level - ability to explain technical concepts clearly is essential Nice to have: Experience using KNIME, Spotfire, or DXP for analysis or tool development Familiarity with UML for system or algorithm modeling Ability to explain complex technical concepts in both Japanese and English Experience with simulation techniques using physical models related to semiconductor processes Benefits Hands-on ownership of machine learning applied to real semiconductor equipment Work on automation and autonomy initiatives with direct production impact Long-term engagement with a leading Japanese semiconductor manufacturer A role combining data science, systems thinking, and customer collaboration Clear progression toward technical leadership and architect-level responsibilities DE&I We value diversity, equity, and inclusion in our workplace. We encourage applications from talented individuals of all backgrounds, experiences, and identities. Your unique skills and perspectives will contribute to smarter decision-making and stronger outcomes for our stakeholders and clients. Bring your authentic self and be part of our journey.

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Responsibilities

Analyze data generated by semiconductor manufacturing equipment and develop machine learning algorithms for various applications. Integrate these algorithms into tools and control systems while coordinating with internal teams and customers.