AI Data Scientist
Tasks
- Build data pipelines
- Create monitored applications
- Deploy machine learning models
- Design evaluation frameworks
- Develop machine learning models
- Develop retrieval and search systems
- Engineer features
- Evaluate factual accuracy
- Implement batch pipelines
- Improve documentation and tooling
- Monitor model performance
- Partner with stakeholders to iterate models
- Perform data cleaning and transformation
- Productionize models with APIs
- Translate research questions into data science problems
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Batch Processing | Data Quality | Data Quality Testing | Embeddings | Experimental Design | Feature Engineering | LLM | Language Processing | Machine Learning | Monitoring | Natural Language | Natural Language Processing | NumPy | Pandas | Prompt engineering | PyTorch | Python | Quality testing | Reproducibility | Retrieval-Augmented Generation | SQL | Scikit-learn | Statistical modeling | Uncertainty | Validation | Vector Search
Education
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