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Regional Information Management Specialist( Re - Advertisement)

Closing: May 22, 2024

2 days remaining

Published: May 9, 2024 (12 days ago)

Job Requirements

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Work experience:

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Job Summary

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The Danish Refugee Council (DRC) and the wider international humanitarian community possess a robust understanding of the causes and effects of conflict disasters through data modelling there is still an underutilization of such models to anticipate and predict conflict events. In West Africa, the West Africa Context Analysis and Foresight Initiative (WACAFI) has been developed as a forecasting model that predicts potential community displacement and helps to inform humanitarian response. However, the capacity to take action from such forecasts remains limited. To address this, DRC aims to amalgamate community-led data gathering and disaster predictive modelling, creating anticipatory action mechanisms that can help prepare for and anticipate population movements resulting from conflict disasters. The project intends to refine the predictive model to incorporate community-level data, test the model in two contexts in the Sahel and East Africa, and develop a global framework that showcases the effectiveness of the disaster predictive model for the wider humanitarian community

The IM Specialist will be responsible for collecting, analysing, and disseminating information related to displacement predictions modelling and information management for Danish Refugee Council (DRC) EAGL Regional Office. The successful candidate will support the organization's efforts to protect vulnerable populations, anticipate, prepare for, and respond to displacement crises. They will work closely with the organization's teams to ensure that accurate and timely information is available for decision-making.

About you

In this position, you are expected to demonstrate DRC’s five core competencies:

  • Striving for excellence: You focus on reaching results while ensuring an efficient process.
  • Collaborating: You involve relevant parties and encourage feedback.
  • Taking the lead: You take ownership and initiative while aiming for innovation.
  • Communicating: You listen and speak effectively and honestly.
  • Demonstrating integrity: You act in line with our vision and values.

Education:

  • Bachelor's degree in data science, statistics, computer science, or a related field
  • Certification in R Program or Python or a relevant data analytics course

Experience and technical competencies:

  • Fully conversant with a programming language – either R Program or Python
  • Experience in developing predictive models is mandatory
  • At least 3 years of experience in information management, data management, statistics, , or a related field
  • Knowledge of establishing and maintaining Information Management or Data Management Systems
  • Experience working in humanitarian contexts and fieldwork in South Sudan is a plus
  • Demonstrated experience with electronic data collection procedures and solutions (ODK, Kobo, Qualtrics, ONA, SurveyCTO etc).
  • Excellent analytical skills and attention to detail
  • Dashboard development preferably using PowerBI
  • Ability to work in a fast-paced environment and handle multiple tasks simultaneously
  • Knowledge of SQL and GIS software is an added advantage.
  • Excellent communication skills in English is required
  • French language would be an advantage


Responsibilities

The Danish Refugee Council (DRC) and the wider international humanitarian community possess a robust understanding of the causes and effects of conflict disasters through data modelling there is still an underutilization of such models to anticipate and predict conflict events. In West Africa, the West Africa Context Analysis and Foresight Initiative (WACAFI) has been developed as a forecasting model that predicts potential community displacement and helps to inform humanitarian response. However, the capacity to take action from such forecasts remains limited. To address this, DRC aims to amalgamate community-led data gathering and disaster predictive modelling, creating anticipatory action mechanisms that can help prepare for and anticipate population movements resulting from conflict disasters. The project intends to refine the predictive model to incorporate community-level data, test the model in two contexts in the Sahel and East Africa, and develop a global framework that showcases the effectiveness of the disaster predictive model for the wider humanitarian community

The IM Specialist will be responsible for collecting, analysing, and disseminating information related to displacement predictions modelling and information management for Danish Refugee Council (DRC) EAGL Regional Office. The successful candidate will support the organization's efforts to protect vulnerable populations, anticipate, prepare for, and respond to displacement crises. They will work closely with the organization's teams to ensure that accurate and timely information is available for decision-making.

About you

In this position, you are expected to demonstrate DRC’s five core competencies:

  • Striving for excellence: You focus on reaching results while ensuring an efficient process.
  • Collaborating: You involve relevant parties and encourage feedback.
  • Taking the lead: You take ownership and initiative while aiming for innovation.
  • Communicating: You listen and speak effectively and honestly.
  • Demonstrating integrity: You act in line with our vision and values.

Education:

  • Bachelor's degree in data science, statistics, computer science, or a related field
  • Certification in R Program or Python or a relevant data analytics course

Experience and technical competencies:

  • Fully conversant with a programming language – either R Program or Python
  • Experience in developing predictive models is mandatory
  • At least 3 years of experience in information management, data management, statistics, , or a related field
  • Knowledge of establishing and maintaining Information Management or Data Management Systems
  • Experience working in humanitarian contexts and fieldwork in South Sudan is a plus
  • Demonstrated experience with electronic data collection procedures and solutions (ODK, Kobo, Qualtrics, ONA, SurveyCTO etc).
  • Excellent analytical skills and attention to detail
  • Dashboard development preferably using PowerBI
  • Ability to work in a fast-paced environment and handle multiple tasks simultaneously
  • Knowledge of SQL and GIS software is an added advantage.
  • Excellent communication skills in English is required
  • French language would be an advantage


Anticipatory Action (AA) Initiative

  • Develop and maintain displacement prediction models using relevant tools and techniques
  • Conduct data pre-processing and data wrangling using R Program or Python
  • Develop and produce regular reports on displacement trends, necessary visualizations, maps and other visual aids
  • Attend relevant meetings and conferences to stay abreast of the latest developments in protection information monitoring and displacement predictions modelling.
  • Participate in the organization's emergency response efforts as needed

Information Management

  • Establish and continuously enhance an information management system tailored to the Regional Office's specific needs.
  • Support Country Offices to establish/strengthen their information management systems
  • Build capacity within the organization by conducting trainings and workshops on information management best practices.
  • Collaborate with program managers and technical teams to integrate information management into project design and implementation.
  • Monitor, organize and manage data collected and analyse trends and relevant indicators that will inform decision making
  • Produce information products such as monitoring reports, dashboards and infographics for use by both internal and external stakeholders

MEAL Support

  • Implement monitoring and evaluation frameworks for projects to track progress against objectives and indicators.
  • Support the dissemination of learning products internally and externally to contribute to sector-wide knowledge development.
  • Provide technical assistance and capacity-building support to field staff on data collection, analysis, and management
  • Monitor utilization of community feedback mechanisms to ensure beneficiary participation, accountability, and responsiveness.


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