Senior Data Scientist
Tasks
- Apply GITOps practices
- Apply prompt engineering best practices
- Build data and analytics pipelines
- Collaborate with clinical stakeholders on hypotheses
- Conduct statistical analysis on clinical datasets
- Deploy solutions on cloud platforms
- Design predictive modeling solutions
- Develop and deploy ML and AI systems
- Ensure computational efficiency
- Implement LLM and RAG based workflows
- Perform exploratory data analysis
- Present findings with visualizations and narratives
- Translate data into actionable insights
- Use MLOps versioning and documentation
- Use Spark for big data processing
Perks/Benefits
Skills/Tech-stack
AWS | Agentic AI | Airflow | Artificial Intelligence | Autogen | Azure | Clinical trials | Clustering | Dagster | Data Governance | Data pipeline | EHR | EMR | Experimental Design | GitHub | GitOps | HIPAA | Hypothesis Testing | Kedro | LLM | Langchain | Llamaindex | MLOps | Machine Learning | Model Explainability | Monte Carlo | Monte Carlo Simulation | OpenAI Agents | Prompt engineering | PySpark | Python | R | RAG | Real-World Evidence | Regression | Series forecasting | Spark | Survival analysis | Time Series | Time Series Forecasting | XAI
Education
Associate Degree | Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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