Senior Data Scientist
Tasks
- Apply MLOps standards for reproducibility and model registries
- Communicate model findings to non technical stakeholders
- Define hypotheses and evaluation metrics
- Deploy models into production
- Develop train validate and tune predictive models
- Drive adoption through training and documentation
- Implement model monitoring for drift performance and data quality
- Perform exploratory data analysis and feature engineering
- Run experimentation with cross validation and bias fairness checks
- Translate business problems into analytics and machine learning use cases
Perks/Benefits
Skills/Tech-stack
AWS SageMaker | Azure Machine Learning | CI/CD | Causal Inference | Classification | Data Analysis | Data Drift | Databricks | Deep learning | Experimental Design | Explainable AI | Exploratory Data Analysis | Feature Engineering | Generative AI | Language Models | Large Language Models | MLflow | Machine Learning | Model Deployment | Model Monitoring | Model registries | Pandas | PyTorch | Python | Regression | Responsible AI | SQL | Scikit-learn | Statistics | TensorFlow | Time Series
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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