General Summary
1) Data Collection
- Train Research Assistants in conducting data collection including quantitative data, qualitative data and costing data.
- Conduct costing data collection
2)Data cleaning and quality assurance
Data Cleaning:
- Perform data cleaning activities to eliminate duplicate records and resolve inconsistencies.
- Review and validate data transformations, including data recording and standardization.
- Develop and maintain standardized procedures for data cleaning and validation
Data Verification and validation
- Conduct thorough verification of data collected from various sources.
- Ensure data accuracy and consistency of the entered data.
- Identify and correct data discrepancies, errors, and outliers.
- Implement data validation checks and rules to identify potential data entry errors.
- Collaborate with data entry personnel to resolve data quality issues.
- Maintain documentation of data quality control processes and outcomes.
- Training Research Associates on data quality assurance.
3) Preliminary Analysis:
- Summarize and aggregate data to create descriptive statistics, including frequencies and distributions.
- Generate graphical representations of data, and prepare summary reports.
- Conduct exploratory data analysis (EDA) to identify patterns, trends, and outliers.
- Assist in the development of data analysis plans and research methodologies.
- Assist in generating preliminary findings and visualizations for research presentations.
- Contribute to the creation of preliminary research reports and presentations.
- Collaborate with the data team to interpret preliminary findings.
4)Reporting
- Work collaboratively with colleagues and stakeholders to ensure effective communication of findings.
- Prepare reports and presentations that summarize data analysis and insights for diverse
Key Responsibilities
Summarize and aggregate data to create descriptive statistics, including frequencies and distributions.
Generate graphical representations of data, and prepare summary reports.
Conduct exploratory data analysis (EDA) to identify patterns, trends, and outliers
Conduct thorough verification of data collected from various sources.
Ensure data accuracy and consistency of the entered data.
Identify and correct data discrepancies, errors, and outliers.
Implement data validation checks and rules to identify potential data entry errors.
Collaborate with data entry personnel to resolve data quality issues.
Maintain documentation of data quality control processes and outcomes.
Training Research Associates on data quality assurance
Academic Qualifications
- Bachelor’s degree in Statistics with bias in Quantitative Economic
- Master’s degree in Public Health
- Statistical Packages: STATA or R programming
Person Specification
Perform data cleaning activities to eliminate duplicate records and resolve inconsistencies.
Review and validate data transformations, including data recording and standardization.
Develop and maintain standardized procedures for data cleaning and validation.
Train Research Assistants in conducting data collection including quantitative data, qualitative data and costing data.
Conduct costing data collection.
