Vehicle Prognostics - Applied Data Scientist
Tasks
- Apply causal inference for root cause identification
- Build physics informed machine learning models
- Create digital signal processing pipelines
- Deploy edge prognostic models in C++
- Design prognostics and remaining useful life frameworks
- Develop prognostic features end to end
- Implement diagnostic code on production vehicles
- Ingest and process vehicle telemetry data
- Perform multi sensor fault detection and isolation
- Run end to end pipeline from simulation to production
- Validate models using hardware in the loop and prototypes
Perks/Benefits
- Child care support
- Community service time
- Employee resource groups
- Flexible family care days
- Medical, dental & vision coverage
- Paid Holidays
- Paid parental leave
- Paid time off
- Prescription Drug Coverage
- Tuition assistance
- Vehicle discount program
Skills/Tech-stack
ANOVA | Anomaly Detection | C++ | Causal Inference | Component analysis | Data Processing | Digital Signal | Digital Signal Processing | Embedded Systems | Fault detection | Fault detection and isolation | Hadoop | MATLAB | Machine Learning | Multivariate analysis | Physics-informed machine learning | Principal Component Analysis | Python | Remaining useful life | SQL | Series forecasting | Signal Processing | Simulink | Spark | Time Series | Time Series Forecasting
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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