Expert Data Scientist
Tasks
- Balance performance explainability compliance and cost
- Define evaluation driven development strategy
- Define model monitoring and automated governance
- Define synthetic data and offline experimentation approach
- Design controlled real world validation programs
- Drive adoption of evaluation best practices
- Escalate delivery risk and technical trade offs
- Establish evaluation metrics and validation methodology
- Manage data and ML workload cost and performance
- Mentor data scientists and review evaluation frameworks
- Oversee agile versioned delivery workstreams
- Own measurable improvement before after comparisons
- Present model governance and impact metrics
- Set AI ML platform and MLOps direction on AWS
- Set modeling approach selection standards
- Support audits and regulatory reviews
Perks/Benefits
- Company-paid certifications
- Conference attendance
- Financial consultations
- Legal consultations
- Medical insurance
- Mental health support
- Udemy access
- Workshops
Skills/Tech-stack
AWS | Agile | Amazon SageMaker | Budgeting | Data Governance | Deep learning | Enterprise Architecture | Explainable AI | Generative AI | MLOps | Machine Learning | Model Evaluation | Model Governance | Model Monitoring | Model Validation | Optimization | Regulatory Compliance | Simulation | Statistics | Synthetic data
Education
Roles
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