Junior Data Scientist
WFP celebrates and embraces diversity. It is committed to the principle of equal employment opportunity for all its employees and encourages qualified candidates to apply irrespective of race, color, national origin, ethnic or social background, genetic information, gender, gender identity and/or expression, sexual orientation, religion or belief, HIV status, physical or mental disability.
Job Title: Junior Data Scientist
Type of Contract: Consultancy
Division: RAM-RAMAC
Duty Station (City, Country): Remote work from home station (travel may be required)
Duration: 11 months
BACKGROUND AND PURPOSE OF THE ASSIGNMENT:
The Climate and Earth Observation (ClEO) Unit, part of the Research Assessment and Monitoring (RAM) Division, draws insights from satellite data streams to provide a range of crucial information products in support of WFP food security and aid operations.
The Unit’s diverse work ranges from monitoring of drought or extreme rainfall conditions to detection of changes in infrastructure assets, as well as high granularity assessments of natural hazard impacts, and mapping of cropland and crop types.
The Team’s work draws on a wide variety of Earth Observation data from low resolution, long record, high frequency variables (rainfall, vegetation indices, land surface temperature) to very high (sub-meter) resolution data, as well as high-frequency, field scale resolution multi-spectral and SAR data from Sentinel-1 and Sentinel-2 platforms. Due to the often extremely large data volumes, these are processed at scale on the Team's cloud-based computing infrastructure.
A Data Scientist is sought to join the Data Science function in the Unit and contribute to the development of advanced analytical solutions to serve the above operations as well as make significant contributions to their operational implementation in RAM-C’s cloud computing infra-structure.
ACCOUNTABITLITIES / RESPONSIBILITIES:
The consultant will join the ClEO Unit of the Research, Assessment and Monitoring Division at WFP HQ and work under the supervision of the Data Science Lead in coordination with the Data Engineering team, being responsible for:
1. Data Science: The consultant will leverage statistical, geo-statistical and machine learning techniques to contribute to the analysis of complex climate, environmental and socio-economic data in support of the Unit's products and services. These could involve, for example:
- Advanced EO time series processing such as filtering, decomposition, lag-correlation analysis, and forecasting.
- Methodologies for multi-resolution data fusion (e.g. Landsat / MODIS) and the blending of ground-truth data with remote-sensed signals.
- Analysis of dynamic land cover change patterns relevant for hazard mapping and environmental resource analysis using either classic or machine learning algorithms.
- Coordinating with other team members to transition their work from development to production on cloud-based infrastructure where/if relevant.
2. Teamwork: The Consultant will be a committed and collaborative team member to support knowledge sharing and common practices within the Data Science function. They will also engage in cross-functional relationships with stakeholders in the rest of the Unit to co-design impactful analytical solutions
3. Communication: The Consultant will be responsible for quality code and documentation of their work and will present their results to stakeholders as needed.
DELIVERABLES QUALIFICATIONS AND EXPERIENCE REQUIRED:
Education:
University degree in mathematics, data science, statistics, earth sciences, or another quantitative degree
Knowledge and Skills:
Essential:
- Demonstrated ability to apply statistical methods and/or data science to real world problems.
- Ability and willingness to learn quickly, especially new tools, techniques and software packages.
- Experience in Earth Observation analysis. Demonstrated experience with remote sensing, agricultural, and/or large geospatial data.
- Excellent Python programming skills including experience with data science and raster analysis libraries (eg, (geo-)pandas, numpy, scikit-learn, rasterio, etc.). for use in research, data analysis, and/or modeling.
- Advanced experience in usage of Jupyter Notebook.
Preferred:
- Knowledge of Earth Observation data, in particular MODIS, Landsat, Sentinel-2 and Sentinel-1, and processing using python, open source or off-the-shelf software tools.
- GIS skills and/or experience (QGIS, GDAL, ArcGIS Pro, Google Earth Engine)
- Experience with machine learning algorithms and tools (e.g.,pyTorch, TensorFlow), artificial intelligence, deep learning and predictive analytics.
- Experience using data engineering best practices (e.g. CI/CD, testing, git)
- Experience working with cloud technologies or distributed computing platforms such as AWS, Azure, Google Cloud, etc.
Languages:
Fluent English with excellent technical reporting ability; good spoken and written French is an advantage
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: 26 September 2022
Ref.: VA No. 173231
All employment decisions are made on the basis of organizational needs, job requirements, merit, and individual qualifications. WFP is committed to providing an inclusive work environment free of sexual exploitation and abuse, all forms of discrimination, any kind of harassment, sexual harassment, and abuse of authority. Therefore, all selected candidates will undergo rigorous reference and background checks.
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.
