Senior Data Scientist
Tasks
- Apply statistical methods for model design and interpretation
- Build and maintain ML pipelines
- Build evaluation and monitoring pipelines
- Conduct experimental design for impact measurement
- Design and analyze A/B tests
- Implement model serving and versioning
- Implement uncertainty quantification
- Lead end to end predictive ML development
- Monitor models in production
- Perform data exploration and feature engineering
- Train, validate, and deploy ML models
- Write production-grade Python code
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | B testing | Bayesian Methods | Causal Inference | Docker | Experimental Design | Feature Engineering | Hypothesis Testing | Kubernetes | LightGBM | MLOps | Machine Learning | Model Monitoring | Model Serving | Model versioning | PyTorch | Python | Recommendation Systems | Reinforcement Learning | Scikit-learn | Statistical modeling | Uncertainty Quantification | XGBoost
Education
Roles
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