Principal Data Scientist
Tasks
- Collaborate on systems design and integrations
- Deliver using agile methodologies and continuous feedback
- Develop and maintain secure scalable AWS infrastructure
- Drive end to end lifecycle of AI ML projects
- Ensure interoperability between AI systems and front end and back end platforms
- Identify high-impact generative AI use cases
- Implement MLOps best practices for governance and reproducibility
- Lead design development and deployment of agentic generative AI applications
- Lead design development and deployment of generative AI applications
- Maintain CI CD pipelines and automated testing
- Manage cloud resource allocation cost optimization and compliance
- Mentor junior data scientists and engineers
- Optimize performance using prompt engineering experimentation and A B testing
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS Bedrock | AWS Cloud | AWS Cloud Development Kit | AWS Lambda | AWS cloud development | Agentic AI | Agile | Amazon S3 | Amazon SageMaker | Automated testing | B testing | CI/CD | Cloud Development Kit | Data Engineering | Design Patterns | DevOps | Enterprise Architecture | Experimentation | Generative AI | Git | Infrastructure as Code | JavaScript | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Prompt engineering | Python | SQL | Software Design | Software Design Patterns | Structured outputs | Tool-Calling | TypeScript | Vue | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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