Food and Agriculture Organization of the United Nations (FAO)

Earth Observation (Data Scientist - 2 Positions)

Food and Agriculture Organization of the United Nations (FAO)

Job Description

The FAO-Lesotho Country Office, facilitates, coordinates and manages all technical and advisory services to be provided by FAO in the implementation of the project on: The Establishment of the baseline for the Integrated Catchment Management Project in Lesotho”. The national programme for integrated catchment management in Lesotho is jointly co-financed by the Government of Lesotho and its cooperation partners EU and Germany through technical assistance by GIZ. FAO has been requested to participate and lead the monitoring component of the GIZ support project. The 2 incumbents will be part of the ICM team of the FAO-Lesotho office in Lesotho Maseru. FAO Lesotho is seeking to hire two consultants, one will be Home-Based, one will be based at the FAO-Lesotho office in Lesotho Maseru. Reporting Lines The Consultant will work under the direct supervision of the Programme Coordinator in Lesotho (based in Maseru), the technical supervision of the Technical Adviser and the operational and administrative supervision of the Budget Holder. Tasks and objectives to be achieved: Support the baseline reporting
  • Identify and analyses data system and user requirements

  • Identification of RS based indicators for monitoring rangelands, wetlands, dongas etc

  • Develop the process chains for EO added value products for monitoring of rangelands, wetlands, dongas, etc:

Validated procedures Algorithms and script for direct integration into data processing environment.
  • Creation of datasets using target and response variables identified and conduct the data analysis required by using Deep Learning, Machine Learning and statistical analysis for predicting designated indicators

  • Support the development of the data virtual processing environment integrating the EO added-value products and derived services into an innovative Earth Observation Cloud Platform to support baseline monitoring applications;

Field survey

  • Support the planning of GPS assisted field surveys for collection of training data sate for the Machine learning and Deep Learning Algorithms

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  • Support the development of dedicated mobile/tablet applications for the baseline centralized field data collection plan in order to ensure harmonization and standardization


  • Creation of code base for supplementing field surveys and automation tasks

  • Conduct quality control of data collected for the surveys

 Capacity Development

  • Support the development of the land cover mapping training exercises and other materials for the national and local workshops

  • Support the development of the data collection training exercises and other materials for the national and local workshops

  • Support the organization of the baseline capacity development workshops and carry out training activities

  • Support the preparation, review and translation of manuals, tutorials and other training material for the baseline related activities

 Other support to the FAOLS team

  • Produce content for baseline (texts, maps, figures, etc.), documents and communication materials as requested

  • Assist the team with the preparation of ready-made slides/presentations related to the ICM Programme

  • Perform other related duties as required

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING Minimum Requirements
  • Advanced university degree in Data Science, Informatics, or related fields.

  • Three to five years of relevant experience in EO Data Analysis

  • Working knowledge of English

FAO Core Competencies
  • Results Focus

  • Teamwork

  • Communication

  • Building Effective Relationships

  • Knowledge Sharing and Continuous Improvement

Technical/Functional Skills
  • Extent and relevance of work experience in applying GIS and RS for land cover/land use assessments

  • Familiarity with ArcGis, ArcGis Online, QGIS, Google Earth Engine

  • Expertise in two or more programming languages including Python, R, C/C and Javascript

  • Familiarity with parallel and GPU computation

  • Familiarity with Big Data processing techniques such as Map Reduce

  • Understanding of SLURM

  • Expertise with various Machine Learning and Deep Learning frameworks for image processing such as Tensorflow, Keras, Pytorch, Scikit-Learn and/or Caret

  • Familiarity with advanced Machine Learning and Deep Learning techniques for regression and classification applied to remote sensing

  • Familiarity with different satellite imagery products and imagery such as Sentinel 1, Sentinel 2 and Landsat 8

  • Familiarity with Geospatial processing libraries such as rasterio and gdal

  • Being able to analyse and present data analysis to team members

  • Ability to operate effectively in a team, contributing positively to team operations and working relationships

  • Sound oral and written communication skills

  • Ability to work under pressure and availability to travel developing or transition countries

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