Senior Data Scientist
Tasks
- Build data processing pipelines
- Collaborate with Agile scrum teams
- Create validation frameworks
- Deploy machine learning pipelines
- Design MLOps deployment automation
- Design machine learning models
- Develop predictive analytics solutions
- Ensure data quality and model drift detection
- Implement model lifecycle management
- Maintain technical documentation
- Monitor model performance
- Optimize feature selection and hyperparameter tuning
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Anomaly Detection | Azure DevOps | Azure Machine Learning | Biased Detection | BigQuery | CI/CD | Classification | Clustering | Cross-validation | Data Governance | Data Validation | Data Visualization | Data Warehousing | Databricks | Docker | ETL | Fairness analysis | Feature Engineering | Feature Store | Forecasting | Git | GitHub Actions | Google Vertex | Google Vertex AI | Great Expectations | Hadoop | Hyperparameter Tuning | Jenkins | Kubeflow | Kubernetes | Language Processing | MLOps | MLflow | Machine Learning | Model Monitoring | Model Registry | Model retraining | Natural Language | Natural Language Processing | NoSQL | NumPy | Pandas | PyTorch | Python | R | Recommendation Systems | Regression | Relational databases | SQL | Scikit-learn | Snowflake | Spark | TensorFlow | Unit Testing | Version control | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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