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IRC Crisis Data Analyst - Jobs in Kenya
The IRC's Emergencies and Humanitarian Action Unit
The IRC’s Emergencies and Humanitarian Action Unit (EHAU) oversees IRC’s global acute emergency preparedness and response activities. The mission of the EHAU is to expand and improve IRC’s ability to help affected communities survive in acute emergencies and hard to reach contexts by investing in people, systems, and solutions to complicated humanitarian challenges. The EHAU team achieves this mission through ongoing rigorous risk analysis, investing in capacity strengthening of frontline humanitarians, partnership with local actors, offering collaborative support and technical assistance to teams working in emergencies and hard to reach places, and deploying and supporting world class emergency response staff as they help people affected by acute crisis situations.
Job Overview/Summary:
The Crisis Data Analyst will be a core member of the IRC's Crisis Analysis team, a small team working globally to support the IRC to understand – and thus respond better to – humanitarian crises. Working in partnership with other team members, the wider EHAU department, and colleagues across the IRC, the role will focus on deploying data analysis techniques to help the IRC respond quickly to new emergencies and understand how it can best serve crisis-affected communities.
Major Responsibilities:
Maintain and update the Emergency Classification system (50%)
• Update and refine classification methodology as needed, ensuring the system performs as expected and meets the IRC's evolving needs.
• Carry out periodic updates to back-end data and analysis of Emergency Classification system.
Watchlist (25%)
• Deliver quantitative aspects of the yearly Emergency Watchlist (countries where the IRC believes emergencies are likely to occur in the coming year).
• Collaborate with other members of Crisis Analysis team to review and update Watchlist methodology on annual basis.
• Represent the Watchlist internally and externally.
Process Emergency Classifications (15%)
• Rapidly classify new emergencies using the IRC's internal classification system, to support senior IRC colleagues to allocate emergency response resources. Review classifications processed by other team members. Training on this system will be provided.
• Participate in maintaining Emergency Classification systems, in particular ensuring that timely notifications are issued and that clear records are kept.
• Flag new emergencies that could be classifiable and agree with affected Country Programs how to proceed.
• Most classification requests are handled during working hours, but all members of the team participate in a roster system to share responsibility for monitoring for classification requests at weekends. The Crisis Data Analyst may, very occasionally, be involved in processing and issuing a classification at weekends where this is essential to ensure a timely response to a new emergency.
Other Crisis Analysis projects (10%)
• Contribute to other Global Crisis Analysis output as required, for example by producing simple data visualizations (e.g. Excel pivot charts).
• Stay abreast of latest data analysis approaches and advise on how they could be applied to Crisis Analysis.
Key Working Relationships:
- Position Reports to: Global Crisis Analysis Lead
- Position directly supervises: None
Indirect Reporting: None
Other Internal and/or external contacts: Close working relationships with rest of Crisis Analysis team and EHAU colleagues; foster and maintain relationships with external researchers, academics and other leaders in the field of international emergencies, data analytics and measurement.
Job Requirements:
Education: Graduate degree in Research Science, Statistics, econometrics, epidemiology or related field - or extensive relevant work experience
Work Experience: At least 3-4 years of directly relevant experience in a similar position (quantitative data analysis).
Demonstrated Skills and Aptitudes:
• Superb data preparation, analysis and reporting skills.
• Knowledge of statistical methodologies required, including proficiency in at least one professional statistical software e.g. R, Python, etc..
• Other relevant skills and experience highly valued,

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