Data Analyst
AI summary
Raising The Village is hiring a mid-level Data Analyst to support high-quality data collection, management, analysis, and reporting for program performance and impact measurement. The role requires strong quantitative and analytical skills, proficiency in R, Python, STATA or advanced Excel, and experience with data visualization tools. Based in Uganda with full-time hours.
- Mid-level role requiring 3 years of data management, analytics, M&E, or research experience
- Requires proficiency in R, Python, and/or advanced STATA or MS Excel
- Experience with Power BI, Tableau, Looker Studio, or Shiny preferred
- Full-time position, Monday to Friday, 8 to 5 working hours
- Bachelor's degree in Statistics, Economics, Data Science, or related quantitative field required
AI job guide
Use this guide to check salary signals, requirements, documents, application steps and safety before you apply.
AI salary guide
Not enough public dataNot enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.
Can you qualify for this role?
- Required3+ years of relevant experienceThe job post includes a minimum experience signal.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in driver, cleaning, internshipThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in Not specifiedThe vacancy is associated with this location.
- UnclearComfort with the Full Time contract termsConfirm hours, duration, probation and benefits at the original source.
Documents to prepare
- Likely requiredUpdated CV
- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
- VerifyID or passport only after verifying the employer
Application tips for this job
- Place your strongest Data Analyst evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to BrighterMonday Uganda and the role in Not specified.
- Add concrete examples related to driver, cleaning, internship, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from BrighterMonday Uganda; avoid sending documents to unofficial contacts or copied links.
- Confirm the deadline, interview location and employer contact before sharing personal documents.
- Prepare a polite question about pay, benefits and contract terms for later interview stages.
Source and safety check
- BrighterMonday Uganda
- Original source link available
- Application method is clear
- Deadline not specified
- No major risk signal was detected in the captured text.
Never pay for interviews, shortlisting, medical checks, uniforms, or job placement. Confirm every application at the original source before sharing personal documents. Report suspicious listing.
Interview preparation
- What experience makes you a strong fit for this Data Analyst role in driver, cleaning?
- How have you handled responsibilities similar to those in this job post?
- Are you available to work in Not specified under the listed contract or schedule?
- Prepare examples with clear responsibilities, tools used and measurable outcomes.
- Review the source and research BrighterMonday Uganda before the interview.
Ask what the first priorities will be in the role and how success will be measured.
Similar jobs to consider
Use AI to apply better
After confirming the original source, use Career Assistant to check role fit, tailor your CV and prepare a cover letter or employer message.
Original source description
- R
- Data Analyst
- Raising The Village
- Engineering & Technology
- Today
- New
- Rest of Uganda
- Full Time
- NGO, NPO & Charity
- Confidential
- Share link
- Share on WhatsApp
- Share on LinkedIn
- Share on Facebook
- Share on Twitter
- Share via SMS
Experience
- Level:
- Mid level
- Length:
- 3 years
- Language Requirement:
- English
- Working Hours:
- Full Time - 8 to 5
- Applicant
- Location:
- Uganda
- Job descriptions &
- in data management, analytics, monitoring and evaluation, research, or related fields.
- Technical Requirements.
- Proficiency in R, Python, and/or advanced STATA or MS Excel.
- 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.
Requirements
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
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.
- Log In and Apply
- Important safety tips
- Do not make any payment without confirming with the BrighterMonday Customer Support Team.
- If you think this advert is not genuine, please report it via the Report Job link below.
- Report Job