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Data Science Expert ICPAC Nairobi

Kenya

  • Organization: NORCAP
  • Location: Kenya
  • Grade: Level not specified - Level not specified
  • Occupational Groups:
    • Statistics
    • Information Technology and Computer Science
    • Information and Communications Technology
    • Scientist and Researcher
  • Closing Date: Closed

NORCAP works with national authorities, regional institutions and international organisations to provide expertise in climate change adaptation and mitigation. Among other things, our experts help to green humanitarian operations, improve coordination and increase vulnerable people’s access to clean energy and climate information.

Do you want to be part of ICPAC's (IGAD's Climate Center) vision to be a world-class centre of excellence in climate services for sustainable development in East Africa? ICPAC is a designated Regional Climate Center under the WMO and delivers Climate Services to 11 East African countries. Providing timely early warnings on extreme weather and climate events is at the chore of its mandate.

We are looking for a candidate that can help optimise the climate services value chain, in particular impact-based forecasting in regional Hazards Watch system. This is a 12 month assignment.

Job description:

  • Optimise the climate services value chain in Eastern Africa
  • Support development of regional Hazards Watch system
  • Support development of methodology for automated Impact Based Forecasting (based on hazard forecast, vulnerability and exposure data). Improve risk assessment through strengthened analysis of different sources of weather, climate and socio-economic data
  • Support generation of added value from ICPAC climate products.
  • Support tailoring of climate services: Analyse user data to support tailoring of digital marketing to different use cases to improve service design
  • Optimise the climate services value chain in Eastern Africa including optimization of new climate services developed in energy, water and agriculture.
  • Advise on optimisation of High-Performance Computing Cluster.
  • Generate added-value from ICPAC and international centers forecasts (e.g. GFS) and support bias correction of the forecast model (WRF)

Qualifications and Skills

  • Advanced degree in Computer Science, Engineering, IT, Data Science, Meteorology or Climate Sciences with knowledge of data sciences
  • Programming and Software development Skills
    • Experience in scripting and programming languages, preferably Python. Experience with R is desirable.
    • Experience in querying languages including SQL
    • Experience/understanding of web development techniques for supporting development of data driven products. The products you will develop will need to be presented mostly on the web
  • Experience and understanding of statistical and geo-statistical techniques and how to apply them in various contexts including in climate applications
  • Experience and understanding of different machine learning methods and algorithms, when to apply them and how to effectively implement them in Python using the available machine learning packages
  • Experience in applying machine learning techniques in the weather and climate context is an added advantage
  • Ability to describe findings and the way techniques work to audiences, both technical and non-technical
  • Experience in visualization tools like matplotlib, ggplot, d3.js or similar. Knowledge on various dashboarding tools and platforms like Tableau is desired.
  • Experience in disaster risk analysis is desirable
  • Fluenc in written and oral English is a requirement

Application procedures and CV registration:

  • Kindly submit your CV and application in English and include your full name as written in your passport.
  • It is expected that you build a CV in our recruitmentsystem by completing your personal information, education, professional work history, language skills and other relevant sections in the fields available. Attached CV's will not be reviewed.

https://www.aplitrak.com/?adid=ay5mZXlsaW5nLjE3Mjk1LjM4MzBAbnJjb3VuY2lsLmFwbGl0cmFrLmNvbQ

This vacancy is now closed.
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