Senior Manager, Data Science
Tasks
- Apply deep learning with transformers
- Apply signal processing and signal detection
- Apply statistical longitudinal modeling for repeated measures
- Build and maintain Python pipelines for wearable time series data
- Collaborate with clinical statistics engineering and product stakeholders
- Collaborate with external partners for QC and validation
- Conduct exploratory data analysis and signal characterization
- Develop and validate models for longitudinal sensor data
- Engineer features from clinical concepts
- Handle within subject dynamics and missingness
- Implement nested cross validation and LOO evaluation
- Impute missing data
- Perform time series QC preprocessing and artifact removal
- Use digital filtering and representation learning
- Use frequency and time frequency representations
- Use reproducible experimentation and documentation
Perks/Benefits
Skills/Tech-stack
AWS | Circadian Cosinor Modeling | Cross-validation | Data Analysis | Deep learning | Digital Signal | Digital Signal Processing | Euler angles | Exploratory Data Analysis | Feature Engineering | Frequency analysis | GPU Computing | Git | Hierarchical models | Imputation | Leave One Out | Machine Learning | Mixed-effects | Mixed-effects models | Nested Cross Validation | Object-Oriented | Object-oriented design | Out of Bag | Parallel Computing | Python | Quaternions) | Reproducible Research | Signal Detection | Signal Processing | Sleep Analytics | Time Series | Time-Frequency | Time-Frequency Analysis | Transformers
Education
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