Data Scientist
Tasks
- Apply advanced statistical methods
- Build reproducible machine learning workflows
- Conduct exploratory data analysis
- Develop validate deploy machine learning and AI models
- Document methods, assumptions, and results
- Implement model monitoring performance tracking and retraining
- Orchestrate model deployment and integration with engineering teams
- Participate in agile ceremonies and continuous improvement
- Perform feature engineering model evaluation and interpretability analysis
- Present analytical findings to stakeholders
- Use cloud analytics services for scalable analytics and ML workloads
Perks/Benefits
- Dental insurance
- Disability insurance
- Flexible spending accounts
- Health insurance
- Life insurance
- Paid time off
- Retirement plan
- Vision insurance
Skills/Tech-stack
AWS Glue | AWS S3 | Agile | Amazon SageMaker | Apache Spark | Artificial Intelligence | Azure Data | Azure Data Factory | Azure Machine Learning | Azure Synapse | Azure Synapse Analytics | CI/CD | Classification | Clustering | Data Analysis | Data Factory | Data Governance | Data Quality | Data Visualization | Databricks | Exploratory Data Analysis | Feature Engineering | MLflow | Machine Learning | Metadata Management | Model Evaluation | Model Interpretability | Model Monitoring | Power BI | Predictive Modeling | Python | R | Regression | SQL | Series analysis | Statistics | Survival analysis | Synapse Analytics | Time Series | Time Series Analysis | Versioning
Education
Roles
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