Data & Signal Analysis Scientist - Q
Core
Scientist who turns experimental results into deep physical insight by analyzing multi-source datasets to uncover connections between signals, features, and system-level performance metrics.
Role type
Senior IC data & signal analysis scientist
Builds
Scalable, reproducible data analysis pipelines and models explaining/predicting performance from signal/feature inputs
Domain
Hardware, machine learning, and signal processing for communication technologies
Deliverable
production ML models
Required skills
Signal processing (time-frequency analysis, noise, coherence, filtering), Large-scale data analysis, Experimental physics and measurement systems interpretation, Statistics (hypothesis testing, regression, uncertainty estimation, feature selection), Causal analysis (ablations, separating effects from correlations)
Preferred skills
Machine learning frameworks (scikit-learn, PyTorch) and model interpretability, Optical/photonic/sensor data experience, Distributed/high-volume data processing, Hands-on lab experience
Technologies
PyTorch, scikit-learn
Responsibilities
Analyze large, multi-source datasets of signals and features; Find and quantify relationships between signal characteristics, extracted features, and performance outcomes; Apply non-linear and data-driven methods to uncover effects that linear analysis misses; Build and validate models that explain or predict performance from signal-level and feature-level inputs; Assess data quality and measurement uncertainty; Recommend which measurements or experiments to run next; Separate causal effects from correlations through ablations and structured analysis; Present findings and recommendations clearly to physics, algorithm, and systems teams; Flag inconsistencies in the physics or the data early
Seniority
Senior, hands-on IC
