Senior Data Scientist – Prognostic and Health Monitoring (HUMS)
Tasks
- Analyze time series sensor telemetry
- Build cumulative damage and fatigue models
- Build physics informed predictive models
- Design end-to-end data pipelines
- Detect anomalies and early faults
- Develop health algorithms
- Drive machine learning tooling innovation
- Map component degradation and remaining useful life
- Support flight and field validation
- Track component usage metrics
- Validate health and prognostic models
- Write production-grade Python code
Perks/Benefits
- 401k match
- Employee stock purchase plan
- Healthcare benefits
- Life insurance
- Long-term disability
- Paid time off
- Short-term disability
Skills/Tech-stack
APIs | Anomaly Detection | Apache Spark | Automated Data Labeling | CI/CD | Data Pipelines | Data labeling | Databricks | Deep learning | Fault isolation | Frequency domain | Git | Machine Learning | Machine Learning Pipelines | Neural Networks | NumPy | Pandas | PostgreSQL | Probability | PySpark | Python | Regression | Relational databases | SQL | SciPy | Series analysis | Signal Processing | Statistics | Time Series | Time Series Analysis
Education
Roles
Regions
Countries
States
Cities
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