Data Analysis
Conduct data analysis for African youth initiatives and report findings.
This opening expired 1 year ago.
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Overview
Conduct data analysis for African youth initiatives and report findings.
You have:
- Experience with thematic analysis tools like NVivo, MAXQDA, or Atlas.ti.
- Proficiency in sentiment analysis tools such as MonkeyLearn or Lexalytics.
- Expertise in statistical tools like Excel, R, or Python for data analysis.
- Ability to create visual storytelling assets using tools like Power BI, Tableau, or Canva.
Contract
This is a UNV contract. More about UNV contracts.
By the end of the century, almost half of the global population will be African. By 2035, Africa will have the largest and youngest workforce in the world. African youth have a unique opportunity to leverage this energy to drive prosperity and innovation in their communities and across the continent. However, despite this potential, youth voices and perspectives are often absent in decision-making processes and policies affecting Africa’s development. To bridge this gap, the UNDP and UNV are implementing the Faces of Africa campaign. This initiative leverages the power and potential of visual storytelling to: Document the aspirations, experiences, challenges, and solutions from African youth. Communicate accurate, nuanced, and contextualized narratives about Africa. Connect African youth to each other and to national and continental leadership. Cultivate a community of young African leaders.
The analysis will cover the following:
Thematic Analysis: Identifying recurring themes in the stories. Sentiment Analysis: Measuring the emotional tone of the stories. Statistical Analysis: Quantifying thematic occurrences and patterns across demographics such as gender, region, and focus area.
Expected Deliverables
Thematic Report: A detailed breakdown of the main themes, sub-themes, and their frequencies. Sentiment Report: A sentiment analysis report summarizing the emotional tone of the stories. Statistical Report: A statistical analysis report with graphs and charts summarizing the key findings. Visual Storytelling Assets: Infographics, charts, and word clouds to aid in visual storytelling. Final Presentation: A consolidated presentation summarizing the findings and providing recommendations for future initiatives.
Qualitative Analysis Tools: NVivo, MAXQDA, or Atlas.ti for thematic coding and analysis. Sentiment Analysis Tools: MonkeyLearn, Lexalytics, or manual coding for sentiment mapping. Statistical Tools: Excel, R, or Python (pandas, matplotlib) for frequency counts, cross-tabulation, and visualization. Visualization Tools: Power BI, Tableau, or Canva for creating graphs, charts, and visual summaries.
Potential interview questions
| Can you describe a time when you used data analysis to influence decision-making? | The interviewer wants to assess your impact on past projects through your analytical skills. | Highlight specific examples where your analysis led to tangible outcomes or changes. |
| How do you ensure accuracy in your data analyses? | Accuracy is crucial in data analysis; this question gauges your attention to detail. | Pro members can see the explanation. |
| What tools do you prefer for statistical analysis and why? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you give an example of a successful visual presentation you created? | Pro members can see the explanation. | Pro members can see the explanation. |
| How do you handle conflicting data findings while analyzing? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 1 year ago
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Updated 1 year ago
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Source:
unv.org
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