Senior Manager, Data Science
Tasks
- Apply frequency time frequency representations and digital filtering
- Apply longitudinal mixed effects and hierarchical models
- Build and maintain Python pipelines for wearable time series data
- Collaborate with clinical stats engineering and product stakeholders
- Collaborate with external partners for QC and validation of vendor outputs
- Conduct EDA signal characterization and signal processing
- Develop and validate longitudinal sensor data models
- Develop reproducible experimentation and documented codebases
- Implement imputation and feature engineering
- Lead code reviews and technical mentorship
- Mentor team members and raise engineering rigor
- Perform evaluation with nested cross validation LOO and OOB
- Perform time series QC preprocessing and sensor artifact removal
- Use deep learning transformers and or ensembles
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Bayesian statistics | Cross-validation | Data Analysis | Data Imputation | Data Preprocessing | Deep learning | Digital filtering | Domain analysis | Ensemble learning | Exploratory Data Analysis | Feature Engineering | Frequency analysis | Frequency-domain analysis | Git | Hierarchical modeling | Leave One Out | Longitudinal data | Longitudinal data analysis | Mixed-effects | Mixed-effects models | Model Explainability | Multi-GPU | Nested Cross Validation | Object-Oriented | Object-oriented programming | Out of Bag | Parallel Computing | Python | Quantitative modeling | Representation Learning | Series analysis | Signal Processing | Time Series | Time Series Analysis | Time-Frequency | Time-Frequency Analysis | Transformers | Version control
Education
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