Junior Data Scientist - Quality Engineering & AI/ML Implementation
Tasks
- Analyze quality data from enterprise systems
- Build semantic data model understanding
- Collaborate on data pipelines and infrastructure
- Define data assets for quality use cases
- Develop and validate machine learning models
- Document analytical findings model performance and data definitions
- Propose new AI and ML approaches for quality solutions
- Support centralized quality reporting with KPIs
- Translate business quality challenges into ML problem statements
- Use large language models and prompt engineering for quality tools
Perks/Benefits
Skills/Tech-stack
AWS | AWS Lambda | Amazon S3 | Amazon SageMaker | Data Governance | Data Modeling | Data Pipelines | Data models | Deployment | Experiment tracking | Language Models | Large Language Models | MLOps | Machine Learning | Model versioning | NoSQL | Prompt engineering | Python | Responsible AI | SAP | SQL | Salesforce | Scikit-learn | Semantic data | Semantic data models | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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