Data Scientist
Tasks
- Apply natural language processing and retrieval augmented generation
- Build data acquisition and processing workflows
- Continuously improve models and workflows using emerging techniques
- Create evaluation frameworks for automation and AI
- Design and improve data pipelines
- Develop and evaluate machine learning and deep learning models
- Develop cloud-based data solutions on AWS
- Follow CI CD and MLOps guidelines
- Implement data solutions with engineering and product teams
- Onboard and manage workloads on cloud platforms
- Perform web scraping and entity extraction
- Process unstructured documents and documents preprocessing
- Translate data requirements into models and pipeline components
Perks/Benefits
Skills/Tech-stack
AWS | Azure | CI/CD | Cloud Computing | Data Analysis | Data Generation | Data Transformation | Data cleaning | Deep learning | Entity Extraction | Exploratory Data Analysis | Feature Engineering | Git | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | NLP | Natural Language | Natural Language Processing | NumPy | Pandas | Privacy-Preserving AI | Privacy-preserving | Python | RAG | Relational databases | Retrieval-Augmented Generation | SQL | Scikit-learn | Statistics | Synthetic Data Generation | Synthetic data | Web Scraping
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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