Executive/Senior Executive, NUHS Education & Research Office
National University Health System
- Singapore
- Permanent
- Full-time
- Data Sourcing and Integration
- Acquire, organize, and integrate diverse healthcare data sources, including EHRs, claims data, clinical trial data, and public health surveillance data.
- Ensure accuracy and consistency of data by applying knowledge of coding systems like ICD-10 and utilizing SQL for data querying and manipulation.
- Performance Measure: Timeliness and completeness of data integration, accuracy of data queries, and adherence to coding standards.
- Statistical Analysis and Insight Generation
- Conduct advanced statistical analysis, data mining, and visualization techniques to uncover trends, patterns, and insights within healthcare data.
- Utilize statistical software packages (e.g., SAS, R, Python) and data manipulation libraries (e.g., pandas, dplyr) to perform analyses.
- Performance Measure: Accuracy and reliability of statistical analyses, effectiveness of visualization in conveying insights, and ability to derive actionable conclusions.
- Reporting and Communication
- Develop clear and concise reports, dashboards, and presentations to communicate findings and insights to stakeholders.
- Ensure reports are tailored to the audience and adhere to ethical and privacy standards regarding patient confidentiality and data security.
- Performance Measure: Clarity and relevance of reports, effectiveness of communication in conveying insights, and stakeholder satisfaction with reporting.
- Continuous Improvement and Compliance
- Continuously improve data management processes, data quality assessment methods, and reporting methodologies.
- Stay updated on ethical considerations and privacy regulations related to healthcare data handling, ensuring compliance with standards such as HIPAA.
- Performance Measure: Implementation of process improvements, adherence to ethical and regulatory standards, and contribution to overall organizational efficiency and compliance.
- Professional degree in quantitative field such as statistics, mathematics, computer science, epidemiology, public health, or related fields.
- Proficiency in statistical analysis, data mining, and data visualization techniques. Experience with statistical software packages such as SAS, R, or Python for data analysis and manipulation.
- Database Skills: Knowledge of SQL for querying and analyzing healthcare databases.
- Ability to interpret and analyze healthcare data to identify trends, patterns, and insights. Experience in preparing reports, dashboards, and presentations to communicate findings to stakeholders.
- Proficiency in programming languages commonly used in data science, such as Python or R.
- Experience with data manipulation libraries (e.g., pandas, dplyr) and visualization libraries (e.g., matplotlib, ggplot2).