Senior Data Scientist
Tasks
- Build and deploy ML pipelines on AWS
- Build dashboards and data visualizations
- Collaborate in agile teams
- Contribute to agentic AI system design
- Design and build RAG systems
- Develop LLM-powered applications
- Develop NLP solutions
- Establish MLOps best practices
- Evaluate model performance with metrics
- Implement predictive analytics and statistical modeling
- Lead AI and machine learning initiatives
- Mentor data scientists
- Perform data mining and EDA
- Recommend AI strategies for healthcare needs
Perks/Benefits
Skills/Tech-stack
API Development | AWS Glue | AWS SageMaker | Agentic AI | Agile | Amazon DynamoDB | Amazon Redshift | Amazon S3 | Apache Airflow | CI/CD | Data Analysis | Data Mining | Data Modeling | Deep learning | Entity recognition | Exploratory Data Analysis | GitHub | Hypothesis Testing | Jenkins | LLM orchestration | Language Models | Language Processing | Large Language Models | Machine Learning | Model Evaluation | Model Monitoring | Model versioning | Named Entity Recognition | Natural Language | Natural Language Processing | NumPy | Pandas | Probability | Prompt engineering | PyTorch | Python | Regression | Retrieval-Augmented Generation | Scikit-learn | Semantic Search | Statistical modeling | Supervised Learning | TensorFlow | Text Classification | Text Embeddings | Topic Modeling | Unsupervised Learning | Vector Database | Vector Search
Education
Roles
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