Data Scientist
Tasks
- Apply statistical modeling
- Build AI/ML pipelines
- Build LLM-based applications
- Collaborate with data engineering teams
- Conduct hypothesis testing
- Contribute to AI best practices
- Create dashboards and visualizations
- Deploy machine learning models
- Deploy models on AWS
- Design machine learning models
- Develop AI Agent workflows
- Develop deep learning models
- Develop generative AI applications
- Ensure model governance and continuous improvement
- Govern deployed AI models
- Implement ELT pipelines
- Implement RAG systems
- Implement embeddings pipelines
- Manage vector databases
- Mentor junior team members
- Monitor model performance
- Optimize data transformations
- Perform exploratory data analysis
- Perform feature engineering
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | CI/CD | Data Pipelines | Deep learning | Docker | ELT | Embeddings | Feature Engineering | Generative AI | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | MLOps | Machine Learning | Model Governance | Model Monitoring | NumPy | Pandas | Predictive Analytics | PyTorch | Python | R | Reinforcement Learning | Retrieval-Augmented Generation | SQL | Scikit-learn | Scrum | Shell Scripting | Spark | Statistical modeling | TensorFlow | Transformer Models | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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