Senior Data Scientist, Defect Quality & Systems

Samsung Electronics•Austin, TX

4d•$106,000 - $145,000•Onsite

About The Position

We are looking for a Senior Data Scientist who is as passionate about data storytelling as they are about data mining. Your mission is to take terabytes of raw manufacturing data and turn it into a clear, visual narrative. You will be responsible for the entire lifecycle of an insight: from the initial SQL query to the final, polished dashboard or webpage that the factory leadership uses to make million-dollar decisions. As a Senior member of the team, you will serve as a technical lead and a bridge between teams. Beyond your individual contributions, you will drive the successful execution of cross-functional projects, aligning stakeholders across the factory to achieve shared goals. You will also play a pivotal role in the growth of our technical talent, mentoring junior engineers in software best practices and code quality to elevate the overall capability of the team.

Requirements

Expert SQL & Data Architecture: Masterly command of SQL for extracting and aggregating data from diverse, multi-database environments.
Python Data Science Stack: Advanced proficiency in Python, leveraging the NumPy, SciPy, and Pandas ecosystem to solve complex analytical problems.
AI/ML Implementation: Experience architecting models using TensorFlow or PyTorch to drive predictive analytics and data-driven decision-making.
Quantitative Analysis: Strong foundation in rigorous statistical methods, including parametric and non-parametric modeling.
Semiconductor Yield Analytics: Specialized knowledge of semiconductor defect domains (detection, classification, and yield impact) paired with the ability to visualize findings in Tableau or Spotfire.
Frontend Interest: Experience with web-based data delivery tools (Vue / FastAPI) and a passion for clear UI/UX design.

Responsibilities

Drive Actionable Insights in Real-Time: Mine complex datasets within a fast-paced, 24/7 manufacturing environment to identify critical trends and cause for anomalies.
Design Intuitive Data Products: Build high-impact, user-centric dashboards and internal web-based tools (both technical and non-technical stakeholders)
Performance Tuning: Optimizing SQL queries or Python scripts to handle large data, ensuring reports load quickly for users in a time-sensitive environment.
Engineer Robust Systems: Lead the evolution of our analytical tools by modeling complex business logic and upgrading our codebase to professional engineering standards, ensuring that reports remain performant and reliable around the clock.