Disaster Risk Modeling Analyst at Ministry in charge of emergency management (MINEMA): (Deadline 19 August 2024)
Job responsibilities
POSITION: DISASTER RISK MODELING ANALYST Job Title : Disaster Risk Modeling Analyst Position Supervisor : SPIU Coordinator Classification Level : H/2.IV Location : Kigali Position Timeline : 1 year JOB PURPOSE The Disaster Risk Modeling Analyst will be responsible for strengthening the system’s performance for the developed advanced early warning system that predicts and mitigates the impact of natural disasters such as landslides and storms; DUTIES AND RESPONSIBILITIES Under the direct supervision of the Director General of Surveillance and Preparedness with the SPIU Coordinator, the Contractor shall have the following scope of the work: DATA COLLECTION, PROCESSING AND ANALYSIS: ❖ Coordinate extensive field data collection across various regions for ground truth verification of the models’ predictions. Coordinate with regional offices to streamline data gathering efforts. ❖ Analyzing historical data, geological surveys, meteorological data, and other relevant information to understand the frequency, intensity, and distribution of different hazards. ❖ Combine, overlay and display mathematical models generated by the system and process the risk quantifications, ❖ Analyzes data from vulnerability of communities, infrastructure, and ecosystems to various hazards for understanding of their susceptibility to damage and disruption, DATA ANALYSIS, INTEGRATION AND MANAGEMENT: ❖ Ensure seamless integration of data from stakeholder APIs. Regularly assess and troubleshoot data flow processes. ❖ Analyzes hazard risk mapping and quantifying the exposure of assets, such as buildings, roads, and critical facilities, to different types of hazards. MODEL CALIBRATION, THRESHOLDS AND EXPOSURE ANALYSES: ❖ Conduct calibrations of disaster prediction models and provide risk probabilities and quantifications, and generate EW messages, ❖ Enhance the system calibration and ensure risk warning messages are accurate ❖ Analyze model thresholds and outputs and develop suggestions for calibration parameters, ❖ organize calibration review meeting with appropriate modelling experts to ensure the improvement of the models’ predictive accuracy. DASHBOARD DEVELOPMENT: ❖ Design and implement informative dashboards for strategic decision-making. Continuously update dashboard features to reflect real-time data and insights. ❖ Knowledge and skills aligned with combining hazard, vulnerability, and exposure information to estimate the potential impact of disasters including potential casualties, economic losses, and social disruption, ❖ Update the dashboard information and explain system functionalities MODEL ENHANCEMENT: ❖ Innovate and apply improvements to existing disaster models. ❖ Stay abreast of technological advancements and integrate best practices into model development processes. ❖ Collaborate and coordinate various modeling experts to improve or upgrade existing models. ❖ Investigates and assesses potential risk factors arising through different data sets and data analysis, DISSEMINATION AND COMMUNICATION OF WARNING MESSAGES: ❖ Generate system messages and analyze the risk probabilities ❖ Oversee the Early warning generation and dissemination, ❖ Model risk based on different datasets generated by the system ❖ Design and update the structure through which warning messages can be disseminated and communicated, ❖ Collect system information feedback from the emergency responders and selected local community levels and hazard risk monitoring. ❖ Coach, mentor and provide ToT trainings for EWS functionalities to the department staff and other key stakeholders, ❖ Maintain up to date risk exposure information and processing risk control and propose mitigation measures to the management team, ❖ Performs other related duties as assigned or requested. The MINEMA reserves the right to add or change duties at any time, REQUIRED ACADEMIC AND EXPERTISE • At least a master’s degree in a relevant field in mathematical modeling, engineering physics, natural sciences including Geology and meteorology with extensive GIS skills, 3yrs of Experiences, • Demonstrated work experience in data/numerical modeling. • Experience in modeling for disaster risk management, meteorology, or environmental sciences will be highly valued. REQUIRED SKILLS EXPERIENCE • Advanced data analysis skills with the ability to interpret complex datasets and extract actionable insights. • Experience with predictive models is an added advantage. • Experience with Geographic Information Systems (GIS) for spatial data analysis and hazard risk mapping, • Experience with ArcGIS products is of advantage, • Solid Python coding skills for model development, data analysis, and automation of processes. • Model thresholds, system analysis and data automation DURATION This position is offered on a one-year contractual basis, subject to renewal based on performance and project needs. APPLICATION PROCESS Interested candidates are required to submit the following: – A detailed Curriculum Vitae (CV). – Cover letter outlining relevant experience and motivation for applying. – Copies of publications related to risk modeling. – Contact information for at least three professional references. EVALUATION CRITERIA Applications will be evaluated based on: – Relevance of academic qualifications and professional experience. – Depth of skills and expertise in disaster modeling and related technologies. – Quality and relevance of publications. – Interview performance.
Qualifications
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1Master’s degree in Mathematical Modeling
3 Years of relevant experience
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2Master’s degree in Engineering Physics
3 Years of relevant experience
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3Master’s degree in Meteorology with extensive GIS skills
3 Years of relevant experience
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4Master’s degree in Geology with extensive GIS skills
3 Years of relevant experience
Required competencies and key technical skills
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1Experience with geospatial technology including but not limited to ArcGIS, raster analysis or holding a GIS specialized Certification is highly advantageous
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2Advanced data analysis skills with the ability to interpret complex datasets and extract actionable insights.
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3Experience with predictive models is an added advantage.
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4Model thresholds, system analysis and data automation
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5Solid Python coding skills for model development, data analysis and automation of processes.
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