Data Scientist (AI & ML)
Tasks
- Architect train and deploy models
- Automate model retraining and monitoring
- Clean and preprocess data
- Conduct stress testing
- Define and track model performance metrics
- Deploy models to cloud
- Design algorithms for real time inference
- Develop ETL pipelines
- Document methodologies code and model decisions
- Implement model interpretability fairness reliability
- Ingest data
- Integrate models into software platforms
- Maintain version control with Git
- Optimize model performance
- Perform exploratory data analysis
- Present findings to stakeholders
- Run cross validation and A B testing
- Set up CI/CD pipelines
- Translate business requirements into technical specifications
- Write modular Python code
Perks/Benefits
- Collaborative cross disciplinary work environment
- Competitive benefits package
- Flexible work arrangements
- Professional development and certification support
Skills/Tech-stack
A/B | A/B Testing | AWS | Azure | B testing | CI/CD | Computer Vision | Cross-validation | Data Analysis | Data Visualization | Deep learning | Docker | ETL | Exploratory Data Analysis | Feature Engineering | GCP | Git | Hadoop | Kubernetes | Machine Learning | Matplotlib | Model Interpretability | NLP | NumPy | Pandas | Plotly | PyTorch | Python | Real Time | Real-time Inference | SciPy | Scikit-learn | Seaborn | Spark | Statistical modeling | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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