Data Scientist - Data Modeling/analytics
Tasks
- Build AI dashboards
- Build automated workflows
- Build forecasting models
- Build simulation and scenario analysis models
- Collaborate on forecasting and analytics tooling
- Communicate model results to stakeholders
- Conduct exploratory data analysis
- Conduct hypothesis testing
- Deploy machine learning models
- Develop MLOps model pipeline
- Develop machine learning models
- Execute data mining analysis
- Monitor model performance
- Perform feature engineering
- Perform statistical modeling
- Provide model explainability
- Quantify model uncertainty
- Support model deployment
- Translate business requirements into technical specifications
- Validate machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Azure | CI/CD | Data Mining | Databricks | Descriptive Statistics | Docker | Experimental analysis | Feature Engineering | Forecasting | Google Cloud | Hypothesis Testing | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Model Deployment | Model Explainability | Model Monitoring | Model Validation | NLP | Predictive Analytics | PyTorch | Python | Retraining | SQL | Scenario Analysis | Scikit-learn | Sentiment Analysis | Series analysis | Simulation Modeling | Statistics | TensorFlow | Time Series | Time Series Analysis | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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