Data Scientist
Tasks
- Communicate analytical outcomes and tradeoffs
- Deploy production machine learning models
- Design build validate machine learning models
- Design optimize Azure data pipelines and lakehouse structures
- Develop GenAI and LLM use cases
- Document models data flows assumptions decisions
- Engage stakeholders define success criteria prioritize use cases
- Ensure responsible AI with data privacy model security ethics
- Integrate Azure services for data and machine learning
- Lead end to end data science project delivery
- Monitor retrain and govern models
- Translate business problems to data science use cases
- Use Azure Databricks for data processing and feature engineering
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Azure Data | Azure Data Factory | Azure Data Lake | Azure Databricks | Azure Machine Learning | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Factory | Data Governance | Data Lake | Deep learning | Feature Engineering | Fine Tuning | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Fine-tuning | Model Monitoring | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | SQL | Scikit-learn | Statistics | Synapse Analytics | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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