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UNICEF

Data Scientist, Emergency and Climate Change, APRO, Bangkok,Remotely with Travel to Malaysia, 5.56Months, (Open to International Candidates Only) Req#595827

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UNICEF
เทคโนโลยี
กรุงเทพมหานครทำงานทางไกลลงประกาศ 32 วันที่แล้ว
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เกี่ยวกับตำแหน่ง

UNICEF is seeking a Data Scientist to lead data projects, build capacity, and develop data and analytics products, focusing on emergency response tools and an air quality model for Malaysia. The role requires extensive experience in data science, stakeholder engagement, and project management.

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About UNICEF

UNICEF works in over 190 countries and territories to save children’s lives, defend their rights, and help them fulfill their potential, from early childhood through adolescence.

At UNICEF, we are committed, passionate, and proud of what we do for as long as we are needed. Promoting the rights of every child is not just a job – it is a calling.

UNICEF is a place where careers are built. We offer our staff diverse opportunities for professional and personal development that will help them reinforce a sense of purpose while serving children and communities across the world. We welcome everyone who wants to belong and grow in a diverse and passionate culture, coupled with an attractive compensation and benefits package.

Visit our website to learn more about what we do at UNICEF.

For every child, the right to Innovation.

How can you make a difference?

The core objective of this assignment is to co-create or lead on data projects, support capacity building where applicable and developing data & analytics products, primarily using cutting-edge data and data science models to support horizontal initiatives across UNICEF’s core programmes on health, education, WASH and country climate initiatives and in particular the Automated SitRep, a tool that supports the Office of Emergency Programmes with data to support regional and country based emergencies and the Air Quality Model creation for Malaysia.

We are looking for an exceptionally qualified candidate with extensive experience in senior stakeholder engagement, facilitation, and project management, combined with strong expertise in data science.

The ideal candidate should have a solid understanding of data visualization techniques and best practices, particularly within the EAP region as well as previous experience working with UNICEF and also on climate data projects.

They should bring robust data science skills, along with deep knowledge of agile methodologies, user-centered design and data management best practices.

Knowledge of satellite imagery and geospatial data engineering is a plus.

They should also be comfortable working in a dynamic, collaborative team environment and be passionate about contributing to the enhancement of UNICEF's mission by designing frontier data products.

Scope of Work:

The consultancy will deliver six tasks focused on the enhancement, testing and scale-up of existing Frontier Data Lab products.

The consultant will work closely with Country Offices, Technology for Development (T4D) colleagues, the Regional Emergency Response Team and the Office of Emergency Programmes.

The consultancy will also strengthen the systems, documentation and workflows required to support effective delivery and future scale-up.

  • Task 1 - Automated SitRep deployment and onboarding
    Support deployment of the Automated SitRep platform in the former SAR Region, including configuration, onboarding of relevant teams and technical support.
  • Deliverable:
    Automated SitRep platform deployed and operational across the former SAR Region, with users onboarded and supporting guidance provided.
  • Task 2 - Automated SitRep testing and enhancement
    Conduct user testing, gather operational feedback and refine the platform to improve usability, automated reporting workflows and system functionality. Document lessons and recommendations for wider scale-up.
  • Deliverable:
    Updated Automated SitRep platform incorporating pilot feedback, with pilot findings, lessons learned and recommendations for future scale-up documented.
  • Task 3- Malaysia air quality situation analysis
    Conduct a situation analysis of the air quality landscape in Malaysia, including available data sources, government systems, institutional arrangements and potential programme applications.
  • Deliverable:
    Malaysia air quality situation analysis documenting the existing landscape, available data and systems, programme opportunities and key considerations for implementation.
  • Task 4 - Malaysia air quality technical and performance assessment
    Assess the suitability and current performance of the regional Air Quality pipeline for application in Malaysia, including data quality, infrastructure requirements, operational constraints, model performance and scalability.
  • Deliverable:
    Technical assessment setting out key findings, constraints, technical requirements and recommendations for adapting and scaling the Air Quality pipeline in Malaysia.
  • Task 5- Malaysia air quality pipeline development
    Develop and configure the initial Air Quality data pipeline for Malaysia, including data ingestion, preprocessing, integration and associated technical workflows.
  • Deliverable:
    Initial operational Air Quality pipeline for Malaysia, with relevant data sources integrated and core ingestion and preprocessing workflows established.
  • Task 6- Air quality model enhancement and testing
    Enhance interpolation and modelling approaches and undertake preliminary testing to improve the accuracy, geographic coverage and operational reliability of the Malaysia pipeline. Document technical approaches and recommendations for further development and regional scale-up
  • Deliverable:
    Enhanced pipeline with preliminary model outputs and testing results, supported by technical documentation and recommendations for further development and scale-up.

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มากกว่า 10 ปี
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ใบรับรอง / ทักษะเพิ่มเติม
[object Object]Data ScienceProject ManagementStakeholder EngagementData VisualizationData EngineeringAgile MethodologiesUser-centered DesignGeospatial DataSatellite ImageryMachine LearningLarge Language ModelsComputer VisionDeep LearningTableau

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