Principal Data Scientist
Tasks
- Architect forecasting tools and platforms
- Build simulation and scenario evaluation capabilities
- Deploy and monitor models with explainability
- Develop statistical Bayesian machine learning forecasting models
- Integrate forecasts into business workflows
- Mentor and upskill junior team members
- Own end to end modeling lifecycle
- Perform causal inference and analytics
- Quantify uncertainty for decision making
- Research evaluate emerging forecasting methods
Perks/Benefits
- Annual bonus program
- Award Winning Time Off
- Dental insurance
- Flexible work model
- Health insurance
- Hybrid work
- Life and disability insurance
- Remote work
- Retirement and savings plan
- Stock-based long-term incentives
- Vision insurance
Skills/Tech-stack
Bayesian Modeling | CI/CD | Causal Inference | Explainability | Feature Engineering | Hierarchical Forecasting | MLOps | Machine Learning | Model Deployment | Model Monitoring | Multi level forecasting | Probabilistic Programming | PyTorch | Pymc | Python | SQL | Scikit-learn | Series analysis | Series forecasting | TensorFlow | Time Series | Time Series Analysis | Time Series Forecasting
Education
Associate Degree | Bachelor of Science | High School Diploma | Master of Science
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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