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Information technology, software development, data jobs in Mbarara, Uganda
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Raising The VillageProfession
Industry (Information technology, software development, data)
Seniority (Information technology, software development, data)
© Fuzu Ltd
Raising The Village
Non-profit + 1 more
Description
The Data Analyst supports RTV in collecting, managing, analyzing, and reporting high-quality data to inform decision-making, improve program performance, and measure outcomes and impact. Working closely with program, Monitoring, Evaluation and Applied Learning, and Product Development teams, the role ensures that data collected is relevant, accurate, reliable, and effectively used for performance monitoring, learning, accountability, and evidence-based decision-making. The Data Analyst provides technical support across data collection planning, questionnaire development, data quality assurance, monitoring and evaluation, research, and impact assessment. The role requires strong quantitative and analytical skills, a solid understanding of monitoring and evaluation frameworks and methodologies, proficiency in data visualization and reporting, and the ability to translate complex data into clear, actionable insights and recommendations for diverse stakeholders.
Professional Requirements.
- Bachelor’s degree in Statistics, Economics, Quantitative Economics, Data Science, or another related quantitative discipline.
- A postgraduate qualification in Monitoring and Evaluation, Statistics, Economics, Data Science, Project Planning and Management, or a related field is an added advantage
- At least 3 years of experience in data management, analytics, monitoring and evaluation, research, or related fields.
Technical Requirements.
- Proficiency in R, Python, and/or advanced STATA or MS Excel.
- Experience with data visualization tools such as Power BI, Tableau, Looker Studio, or Shiny etc
- Strong understanding of data management, data quality assurance, and analytical workflows.
- Familiarity with experimental and quasi-experimental evaluation methods.
- Ability to synthesize quantitative and qualitative evidence into actionable insights.
Responsibilities
Data Analysis and Insights Generation
- Analyze and interpret data to generate actionable insights that support program performance and strategic decision-making.
- Identify trends, patterns, and key drivers of performance through quantitative and qualitative analysis.
- Translate analytical findings into clear recommendations for technical and non-technical stakeholders.
- Contribute to organizational learning by synthesizing evidence and supporting data-driven decision making.
- Impact Evaluation and Research Support
- Support the design and implementation of evaluations, assessments, surveys, and research activities.
- Contribute to the development of evaluation methodologies, sampling approaches, and analytical frameworks.
- Support the measurement of program outcomes and impact through rigorous analytical approaches.
- Summarize and communicate research findings to inform program improvement and learning.
Dashboard Development, Data Visualization, and Reporting
- Develop and maintain dashboards, visualizations, and reporting products for internal and external
- stakeholders.
- Prepare analytical reports, presentations, and data summaries.
- Transform complex data into clear, compelling, and actionable insights.
- Promote the effective use of data for performance monitoring and decision-making.
- Data Collection Design and Tool Development
- Support the design and implementation of data collection methodologies aligned with program objectives and monitoring and Evaluation frameworks.
- Development and refinement of data collection instruments and performance measurement tools.
- Support the development of data management guidelines, training materials, and standard operating procedures.
- Continuously improve data collection processes to enhance data quality and usability.
Data Management and Quality Assurance
- Manage the data lifecycle, including cleaning, validation, storage, analysis, and reporting.
- Implement data quality assurance processes to ensure accuracy, completeness, consistency, and
- reliability of data.
- Support data governance and compliance with organizational data management standards.
- Identify and resolve data quality issues to ensure the availability of high-quality data for decision-making.
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