Data Scientist
Tasks
- Analyze structured and unstructured data
- Build automated data pipelines
- Build data extraction and aggregation workflows
- Clean normalize and validate data
- Coordinate requirements with stakeholders
- Design machine learning models
- Design natural language processing pipelines
- Develop business intelligence reports
- Develop visualization solutions
- Engineer data analytics solutions
- Evaluate data security and continuity of operations
- Extract evaluate interpret and visualize data
- Integrate diverse data sources
- Maintain model training evaluation and deployment
- Perform ETL strategies
- Prepare technical documentation and test plans
- Prototype proof of concept and implement models
- Support troubleshooting and application efforts
- Test debug and document code
Perks/Benefits
Skills/Tech-stack
AWS | Agile | Artificial Intelligence | Azure | Azure Data | Azure Data Factory | Azure DevOps | Continuous Delivery | Continuous Integration and Continuous Delivery | Continuous integration | Data Analytics Expressions | Data Factory | Data Governance | Data Lake | Data Lakehouse | Data Mining | Data Quality | Data Security | Data Visualization | Data Warehouse | Data access | Data analytics | Databricks | ETL | Experiment design | GitHub | Hypothesis Testing | JDBC | Language Processing | Machine Learning | Natural Language | Natural Language Processing | ODBC | Pattern Recognition | Power Apps | Power Automate | Power BI | Power Platform | Predictive Analytics | Process Automation | Python | R | REST API | Relational databases | Robotics Process | Robotics Process Automation | SQL | Statistical Analysis | Text Mining | Web Scraping
Education
N/A
Roles
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