Senior Wafer Process Analytics Engineer

About the role: you will: Develop advanced analyses to understand and improve critical dimension control, process variation, device geometry, and wafer-level performance. Build predictive and empirical models connecting process inputs, material properties, and metrology results to key process and device outputs. Develop, validate, and deploy AI and machine-learning solutions for process optimization, excursion identification, and downstream prediction. Create automated image-analysis workflows for SEM, optical, AFM, and other characterization data, including segmentation, feature extraction, dimensional measurement, and defect classification. Develop empirical unit-process models and wafer-process simulations that predict geometry evolution, process interactions, and cumulative variation through integrated device flows. Partner with unit process, integration, metrology, and design engineers to translate engineering problems into practical analytical solutions. Design experiments and data-collection strategies that produce reliable training data, isolate key process factors, and support model validation to connect downstream targeting to in-room parametrics. Deploy maintainable engineering tools, scripts, dashboards, or automated pipelines while establishing sound practices for data traceability, version control, and model documentation. Communicate model performance, uncertainty, limitations, and recommendations to technical and management audiences, and contribute to technology transfer and intellectual property.

About you: You are self-motivated, intellectually curious, and energized by solving complex engineering problems with data. You combine strong analytical skills with physical intuition and seek to understand the mechanisms behind statistical relationships. You can translate loosely defined technical challenges into structured analyses, models, experiments, and actionable recommendations. You collaborate effectively across engineering, science, software, and technician teams and communicate complex concepts clearly. You value data quality, reproducibility, model validation, and thorough documentation. You are comfortable working in a combination of cleanroom, laboratory, and office environments. Your experience includes: Strong experience with Python, MATLAB, R, or similar tools for scientific computing, data analysis, model development, and workflow automation. Experience applying statistical methods such as regression, design of experiments, ANOVA, statistical process control, multivariate analysis, or process-capability analysis. Experience developing and validating machine-learning or AI models using engineering, manufacturing, scientific, or image-based data. Experience with image processing or computer vision, including segmentation, feature extraction, classification, object detection, dimensional measurement, or image registration. Experience building process-accurate models and calibrated unit process simulations, using empirical and/or physics informed models on commercial platforms or home-built code. Ability to organize and analyze complex datasets from multiple sources and communicate results through clear visualizations and technical presentations. Bachelor's degree in Data Science, Computer Science, Electrical Engineering, Chemical Engineering, Materials Science, Mechanical Engineering, Physics, Applied Mathematics, Statistics, or a related technical field with 5+ years of relevant experience; a Master's degree with 3+ years; a PhD with 0+ years; or equivalent education and experience. You might also have Experience with semiconductor fabrication, nanotechnology, MEMS, magnetic devices, photonic devices, or advanced manufacturing. Familiarity with lithography, thin-film deposition, plasma or wet etch, CMP, cleans, thermal processing, or wafer-level metrology. Experience analyzing SEM, TEM, AFM, optical microscopy, profilometry, or defect-inspection data. Experience with PyTorch, TensorFlow, scikit-learn, OpenCV, SQL, databases, data pipelines, source control, containerization, or model deployment. Knowledge of model monitoring, retraining, explainability, governance, and responsible AI practices. A record of innovation through patents, invention disclosures, publications, presentations, deployed analytical capabilities, or measurable process improvements.

Location: Seagate's Normandale campus, spanning Bloomington and Edina, MN, serves as the global hub for recording head development and manufacturing. The campus offers an on-site café, fitness center, wellness programs, indoor walking paths, meditation rooms, and frequent cultural and community events. Numerous dining, shopping, and recreational options are located just minutes away. The estimated base salary range for this position is $92,310.40 - $131,876.00. The individual salary is based on work location and additional factors, including job-related skills, experience, and relevant education or training. Seagate offers comprehensive benefits to its eligible employees, including, but not limited to, eligibility to participate in discretionary bonus program, medical, dental, vision, and life insurance, short-and long-term disability, 401(k), employee stock purchase plan, health savings account, dependent care, and healthcare spending accounts. Seagate also offers paid time off, including 12 holidays, flexible time off provided pursuant to Seagate policy, a minimum of 48 hours of paid sick leave, and 16 weeks of paid parental leave. The benefits for this position are based on a full-time schedule for a full calendar year and may differ depending on work location.

Location: Normandale, United States

Travel: Up to 10%