Senior Data Scientist
Tasks
- Apply statistical methods to model design and interpretation
- Build MLOps model serving and evaluation pipelines
- Build and validate ML features and models
- Deploy ML models and monitor performance
- Design and interpret A/B tests
- Implement causal inference and experimental design
- Implement supervised unsupervised learning approaches
- Lead end to end predictive ML development
- Write production Python code with testing
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | B testing | Bayesian Methods | Causal Inference | Deep learning | Docker | Experimental Design | Feature Engineering | Hypothesis Testing | Kubernetes | LightGBM | MLOps | Machine Learning | Model Monitoring | Model Serving | Model versioning | Probability | PyTorch | Python | Reinforcement Learning | Scikit-learn | Statistics | Supervised Learning | Uncertainty Quantification | Unsupervised Learning | XGBoost
Education
Roles
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