By continuing to browse this site, you agree to our use of cookies. Read our privacy policy

Data Scientist Junior Consultant

Italy (Italy)

  • Organization: WFP - World Food Programme
  • Location: Italy (Italy)
  • Grade: International Consultant - Internationally recruited Contractors Agreement - Consultancy
  • Occupational Groups:
    • Statistics
    • Scientist and Researcher
    • Information Technology and Computer Science
  • Closing Date: 2021-09-17

Click "SAVE JOB" to save this job description for later.

Sign up for free to be able to save this job for later.

 

WFP seeks candidates of the highest integrity and professionalism who share our humanitarian principles

 

Selection of staff is made on a competitive basis, and we are committed to promoting diversity and gender balance

 

 

Job Title: Data Scientist

 

Type of Contract: Junior Consultant

 

Division: RAMAH  - Needs Assessment and Targeting Unit

 

Duty Station (City, Country): Remote (home-based)

 

Duration: 9 months

 

 

 

BACKGROUND:

 

The Hunger Monitoring Unit (RAMAH) in WFP’s Research Assessment and Monitoring (RAM) Division manages WFP’s global hunger monitoring systems, building upon the successes of the mobile Vulnerability Analysis and Mapping (mVAM) initiative. This entails the establishment and oversight of WFP’s near real-time food security monitoring systems in close to 40 countries, as well as developing and refining advanced analytical approaches – including predictive analytics capacities – in collaboration with internal and external partners to ensure timely and holistic views of the food security situation globally. Data from these systems flows into the HungerMap LIVE (hungermap.wfp.org), WFP’s global hunger monitoring system. This information is also published through Global and Regional Insights and Key Trends reports and other related resources, enabling decision makers to monitor the situation effectively and adopt early mitigation actions.

RAMAH seeks a consultant to support with the development of a collaborative DLR-WFP-RAM project aiming at expanding the current HungerMap LIVE’s predictive capabilities to forecasting insufficient food consumption up to 3 months in advance. AI has led to a huge progress in the prediction of complex systems, where reservoir computing (RC) is among the most promising AI-approaches. Here, we want to develop a RC-based prediction model using well-suited data sets for two pilot countries. Such an accurate food prediction model would enable WFP and national governments to respond before life-threatening famine strikes. WFP and the humanitarian community would be able to take preventive action thus potentially saving thousands of lives.

 

 

 

ACCOUNTABILITIES/RESPONSIBILITIES:

 

Under the day-to-day supervision of the RAMAH’s Lead Data Scientist, the Consultant will be responsible for the following activities:

 

  • Data Acquisition and preparation for the pilot studies
  • Investigation of the correlation properties of the data
  • Measurement of the linear and nonlinear correlations and causal relations in the data
  • Determination of correlation networks and assessing their predictive power
  • Development of AI-based prediction schemes and assessing their predictive power
  • Groundtruthing model in one country, Extension of the analyses to data second one
  • Assessing generalizability of new model
  • First integration into HungerMap LIVE
  • Perform other tasks as required.

 

 

 

DELIVERABLES AT THE END OF THE CONTRACT:

 

Identification of relevant observational data for selected country

First results for a predictive model based on correlation networks for selected country

First results for a predictive model based on AI forecast for two pilot countries

Forecasting feature implemented in HungerMap LIVE

 

 

QUALIFICATIONS AND EXPERIENCE REQUIRED:

 

Education:

 

Advanced university degree in physics.

 

 

Experience:

 

Experience in research in complex systems theory, network theory, nonlinear data analysis, artificial intelligence or alike is desirable.

 

Knowledge and Skills:

 

  • Complex systems
  • Nonlinear data analysis
  • Networks
  • Artificial Intelligence
  • Programming experience, especially in python
  • Publications in the aforementioned fields of research are a plus

 

Languages:

 

Spoken and written English required.

 

 

 

 

Terms and Conditions

 

WFP offers a competitive compensation package which will be determined by the contract type and selected candidate’s qualifications and experience.

 

Please visit the following websites for detailed information on working with WFP.

 

http://www.wfp.org Click on: “Our work” and “Countries” to learn more about WFP’s operations.

 

 

 

Deadline for applications: 17 September 2021

 

Ref.: VA No. 148922

 

 

Qualified female applicants and qualified applicants from developing countries are especially encouraged to apply

 

WFP has zero tolerance for discrimination and does not discriminate on the basis of HIV/AIDS status

 

No appointment under any kind of contract will be offered to members of the UN Advisory Committee on Administrative and Budgetary Questions (ACABQ), International Civil

Service Commission (ICSC), FAO Finance Committee, WFP External Auditor, WFP Audit Committee, Joint Inspection Unit (JIU) and other similar bodies within the United Nations

system with oversight responsibilities over WFP, both during their service and within three years of ceasing that service.

 

We do our best to provide you the most accurate info, but closing dates may be wrong on our site. Please check on the recruiting organization's page for the exact info. Candidates are responsible for complying with deadlines and are encouraged to submit applications well ahead.
Before applying, please make sure that you have read the requirements for the position and that you qualify.
Applications from non-qualifying applicants will most likely be discarded by the recruiting manager.
Apply

What does it mean?

Click "SAVE JOB" to save this job description for later.

Sign up for free to be able to save this job for later.