Senior Data Scientist
Tasks
- Apply MLOps for CI CD and monitoring
- Balance performance explainability and cost
- Build AI ML platform components on AWS
- Collaborate with stakeholders on initiatives
- Define evaluation metrics
- Define success criteria for modeling
- Deliver measurable improvements
- Generate synthetic and use historical data
- Maintain versioning documentation and change logs
- Optimize compute storage and pipeline efficiency
- Own agile release workstreams
- Run offline experimentation and controlled validation
- Select modeling approach
- Support model governance and audit readiness
- Validate model performance and robustness
Perks/Benefits
- Company-paid certifications
- Financial consultation
- Growth focus
- Internal mobility opportunities
- Legal consultation
- Medical insurance
- Mental health support
- Udemy access
- Workshops and conferences
Skills/Tech-stack
A/B | A/B Testing | AWS Glue | AWS Lambda | AWS SageMaker | Amazon Redshift | Amazon S3 | Automated retraining | B testing | Backtesting | CI/CD | Data Generation | Explainability | GenAI | LIME | MLOps | Machine Learning | Model Monitoring | Model Registry | Optimization | Python | R | SHAP | SQL | Shadow Deployment | Simulation | Statistical modeling | Synthetic Data Generation | Synthetic data
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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