Senior Data Scientist
Tasks
- Automate model lifecycle with MLOps
- Build customer segmentation and recommendation systems
- Build feature pipelines with data engineering teams
- Conduct A/B testing
- Deploy machine learning models to production
- Design predictive machine learning models
- Develop propensity scoring and next best action
- Generate insights using large language models
- Implement uplift modeling and causal inference
- Mentor junior data scientists
- Monitor model performance and drift
- Translate model outputs into business recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS Bedrock | AWS SageMaker | B testing | Bayesian Inference | CI/CD | Causal Inference | Classification | Customer Segmentation | Drift Detection | Ensemble Methods | Feature Store | LightGBM | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Next Best Action | Prompt engineering | Propensity scoring | PyTorch | Python | RAG | Recommendation Engines | Regression | SQL | Sagemaker Pipelines | Scikit-learn | Series analysis | Statistical modeling | TensorFlow | Time Series | Time Series Analysis | Uplift Modeling | XGBoost
Education
Roles
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