Amazon Senior Data Scientist Special Projects 

United States, Washington, Seattle 

125548280

Key job responsibilities
In this role, you will:
- Analyze complex healthcare data to identify patterns, trends, and insights
- Develop and validate statistical methodologies
- Create and maintain analytical frameworks
- Provide recommendations on data collection strategies- Design and implement statistical analyses to validate analytical approaches
- Present findings to stakeholders and contribute to scientific publications- Design and implement causal inference analyses to understand underlying mechanisms
- Develop frameworks for identifying and validating causal relationships in complex systems
- Work with stakeholders to translate causal insights into actionable recommendationsA day in the life
You'll work with large-scale healthcare datasets, conducting sophisticated statistical analyses to generate actionable insights. You'll collaborate with Applied Scientists to validate model predictions and ensure statistical rigor in our approach. Regular interaction with product teams will help translate analytical findings into practical improvements for our services.

- MS or PhD in Statistics, Biostatistics, Data Science, or related quantitative field
- 5+ years of experience applying statistical methods to healthcare data
- Proficiency in Python, R, or similar programming languages for data analysis
- Experience with statistical modeling and analysis of longitudinal data
- Strong background in experimental design and hypothesis testing
- Demonstrated expertise in handling large, complex datasets

- PhD in Statistics, Biostatistics, Data Science, or related quantitative field
- Experience analyzing healthcare data
- Knowledge of healthcare industry regulations and processes
- Familiarity with healthcare data standards
- Publication record in relevant scientific journals
- Experience with distributed computing platforms
- Strong communication skills and ability to present technical concepts to non-technical audiences
- Familiarity with healthcare data standards
- Experience applying causal inference frameworks to real-world problems
- Familiarity with modern causal discovery and inference techniques
- Knowledge of counterfactual analysis methods