Data automation and AI application development
Support design, automation, and enhancement of data pipelines and AI applications.
This opening expired 7 months ago.
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Overview
Support design, automation, and enhancement of data pipelines and AI applications.
You have:
- Design, build, and maintain automated data pipelines using scripting languages and workflow tools.
- Develop reproducible analytical scripts and functions in R for data cleaning, analysis, and reporting.
- Design and develop interactive dashboards using Power BI or similar platforms.
- Develop and deploy AI-enabled applications using Python, including basic machine learning, natural language processing, or automation use cases.
- Integrate AI tools into collaboration platforms such as Slack to support data queries, summaries, or workflow automation.
Contract
This is a UNV contract. More about UNV contracts.
The Online Volunteer will support the design, automation, and enhancement of data pipelines, analytical workflows, and AI-enabled applications under the guidance of the Information Systems and Analytics team. The role will involve close collaboration with public health professionals, epidemiologists, data analysts, and IT specialists to translate analytical needs into automated and AI-supported solutions. The assignment focuses on integrating data from multiple sources, developing reproducible analytics, and deploying dashboards and AI applications to support operational and strategic functions.
The candidate will work under the supervision of the Health Emergency Information Systems Manager. The role requires strong technical skills in data automation, R programming, dashboard development, and applied AI. Experience with Python-based AI tools and collaboration platforms such as Slack is highly desirable.
Key deliverables include:
- Automated data pipelines for ingestion, transformation, and validation of structured and semi-structured datasets.
- Analytical scripts and workflows developed in R to support routine and ad hoc analysis.
- Interactive dashboards (e.g. Power BI) for monitoring, reporting, and decision support. = AI-enabled applications or workflows (e.g. Python-based models, Slack-integrated AI tools) to enhance data analysis, knowledge extraction, and automation of routine tasks.
- Technical documentation and user guidance to support sustainability and knowledge transfer.
Required experience • Data Automation and Pipelines: - Design, build, and maintain automated data pipelines using scripting languages and workflow tools. - Integrate data from multiple sources (APIs, databases, files) with appropriate validation, logging, and error handling. - Ensure data quality, reproducibility, and alignment with organizational data standards.
• R Programming and Analytics: - Develop reproducible analytical scripts and functions in R for data cleaning, analysis, and reporting. - Apply statistical and analytical methods relevant to public health and operational analytics. - Produce reusable code and documentation to support ongoing analytical needs.
• Dashboards and Data Visualization: - Design and develop interactive dashboards using Power BI or similar platforms. - Translate analytical outputs into clear, actionable visualizations for technical and non-technical audiences. - Connect dashboards to automated data sources to ensure timely updates.
• AI and Application Development (Preferred): - Develop and deploy AI-enabled applications using Python, including basic machine learning, natural language processing, or automation use cases. - Integrate AI tools into collaboration platforms such as Slack to support data queries, summaries, or workflow automation. - Apply responsible AI principles, including transparency, data protection, and appropriate use of models within organizational architecture.
Potential interview questions
| How have you implemented automated data pipelines in your previous work? | This question assesses your practical experience with data pipelines. | Detail a specific project, the technologies used, and the results achieved. |
| Describe a time when your R programming skills led to significant analytical insights. | The interviewer wants to understand your technical proficiency and impact. | Pro members can see the explanation. |
| Can you share an experience where you developed a dashboard and the impact it had? | Pro members can see the explanation. | Pro members can see the explanation. |
| What is your approach to ensuring the quality and reproducibility of your analytical work? | Pro members can see the explanation. | Pro members can see the explanation. |
| Explain how you would integrate AI tools into a team workflow. | Pro members can see the explanation. | Pro members can see the explanation. |
| Could you give an example of a project where you used Python for AI application development? | Pro members can see the explanation. | Pro members can see the explanation. |
| How do you stay updated with advancements in data automation and AI development? | Pro members can see the explanation. | Pro members can see the explanation. |
| Describe your experience working in interdisciplinary teams and how it benefited your projects. | Pro members can see the explanation. | Pro members can see the explanation. |
Added 8 months ago
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Updated 7 months ago
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Source:
unv.org
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