Metrology Data Scientist

What you'll do

• Build, calibrate, and validate predictive models and signal-processing approaches for material-property prediction.
• Develop validation frameworks, assess robustness and uncertainty, and prepare models and documentation for production handoff.
• Analyze customer proof-of-concept data, report findings, and use feedback to guide model improvements.

What they ask for

• B.S. in Data Science, Statistics, Applied Mathematics, or a related quantitative science field with 3–5 years of applied ML/data science experience; or M.S. with 1–3 years.
• Hands-on experience building and validating supervised and self-supervised predictive models in Python.
• Ability to analyze multivariate, high-dimensional datasets and perform feature engineering and selection.
• Solid grasp of statistical modeling, including uncertainty quantification, regularization, covariate analysis, and feature importance methods.

Nice to have

• Experience with time-series, spectroscopic, or other sensor-based signal data, or work in a physical-science domain.
• Production model deployment, data pipeline development, customer-facing applications engineering, or fluency in a stakeholder language such as Mandarin Chinese, Japanese, German, or Korean.

Pay

$120,000 — $170,000 USD base salary

Tools

Python, PostgreSQL

AI focus

Apply machine learning to sensor signals and material-property prediction, including regression, dimensionality reduction, probabilistic modeling, anomaly detection, physics-informed ML, uncertainty quantification, and out-of-distribution detection.