Mid Data Scientist
Tasks
- Build evaluate tune supervised models
- Build evaluate tune unsupervised models
- Conduct model evaluation using metrics
- Craft data-driven solutions
- Create data visualizations
- Deploy models with MLOps lifecycle
- Develop analytical and machine learning models
- Engineer features
- Perform exploratory data analysis
- Run ML experimentation
- Support data analysis with SQL
- Validate models using cross-validation
Perks/Benefits
Skills/Tech-stack
AWS SageMaker | Azure Machine Learning | Cross-validation | Data Analysis | Data Visualization | Databricks ML | Exploratory Data Analysis | Feature Engineering | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Hypothesis Testing | MLOps | MLflow | Machine Learning | Matplotlib | Model Deployment | Model Registry | Model Validation | NumPy | Overfitting | Pandas | Plotly | Power BI | Probability | PyTorch | Python | SQL | Scikit-learn | Seaborn | Statistics | Supervised Learning | Tableau | TensorFlow | Unsupervised Learning | Versioning | Vertex AI | Weights and Biases
Education
N/A
Roles
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