Principal Data Scientist - Forecasting
US - California - Thousand Oaks - Field/Remote, United States
R
USD 160K-217K Senior-level Full Time
Tasks
- Apply causal inference
- Build Bayesian models
- Build forecasting platforms
- Create simulation and scenario evaluation
- Deploy and monitor models
- Develop forecasting models
- Develop self service forecasting tools
- Engineer features for forecasting
- Establish forecasting best practices
- Integrate forecasts into business workflows
- Manage end-to-end modeling lifecycle
- Mentor junior team members
- Perform time series forecasting
- Provide model explainability
- Research emerging forecasting methods
Perks/Benefits
- Career development
- Employee benefits
- Flexible work models
- Hybrid work
- Remote work
- Retirement savings plan
- Time off
Skills/Tech-stack
Bayesian Modeling | CI/CD | Causal Inference | Explainable AI | Feature Engineering | Hierarchical Forecasting | MLOps | Machine Learning | Model Deployment | Model Monitoring | Multi level forecasting | Operations Research | Probabilistic Programming | PyTorch | Pymc | Python | SQL | Scikit-learn | Series forecasting | TensorFlow | Time Series | Time Series Forecasting
Education
Associate Degree | Bachelor of Science | High School Diploma | Master of Science | PhD
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
Regions
Countries
States
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