Senior Data Scientist, Innovation Engineering Technology

Job Title

Senior Data Scientist, Innovation Engineering Technology

Role Summary

The Senior Data Scientist will apply statistical modeling, machine learning, and data engineering to develop predictive models and analytic tools that improve manufacturing yield, diagnose root causes, and increase engineering productivity.

The role sits within an AI and innovation engineering team supporting end-to-end data analysis, building scalable data pipelines and algorithms, and integrating AI capabilities into engineering workflows.

Experience Level

Senior-level. Years of experience not specified in the source posting.

Responsibilities

Primary responsibilities include developing AI-enabled analytics and integrating them into engineering processes to drive operational improvements.

• Design and implement algorithms, models, and automated workflows for large, heterogeneous datasets from front-end and back-end testing.
• Perform root-cause analysis, yield optimization, and feature extraction to produce actionable insights for engineering teams.
• Develop and advance AI libraries and algorithms that bridge domain knowledge and engineering needs.
• Collaborate across teams to integrate AI tools into engineering processes and improve engineer productivity.
• Explore and prototype new technologies and research approaches to drive innovation and operational efficiency.

Requirements

Listed below are the core qualifications and additional desirable skills extracted from the posting.

• Must-have — Solid experience in statistical modeling, feature extraction, and machine learning (supervised, unsupervised, semi-supervised).
• Must-have — Proficiency extracting and preparing data from databases (SQL and other query languages), including data cleansing, outlier detection, and handling missing data.
• Must-have — Familiarity with AI tools and platforms (examples cited: Google, Microsoft, OpenAI) and ability to integrate them with big-data workflows.
• Must-have — Strong verbal and written communication skills in English.
• Nice-to-have — Proficiency in Python and/or R; experience with time-series, image data, and semi-supervised learning.
• Nice-to-have — Familiarity with JavaScript/AngularJS, visualization tools (Tableau, Power BI), and Manufacturing Execution Systems (MES).
• Nice-to-have — Prior exposure to the semiconductor or manufacturing domain.

Education Requirements

Not specified.