Internship - Data Science, Vulnerability & Analysis,
Rome
WFP - World Food Programme
Closing date: Thursday, 14 December 2017
Key outputs/Responsibilities:
1. Interfacing with standard WFP data structures and systems
2. Provide inputs in developing bayesian models for WFP indicators
3. Developing a standardized pipeline for performing Bayesian updates on WFP indicators
4. Developing customizable scripts for the incorporation of informative priors and covariates
5. Validating outputs and assistance with ‘ground-truthing’ results
6. Analyzing results and producing reports to include tabular, graphical, and inferential results
7. Maintain and create databases to ensure all data is properly organized and stored
8. Ensure adherence to WFP policies regarding data, including privacy, security, data management, and documenting code
9. Perform any other duties as determined by the supervisor…
Essential Requirements:
- Working knowledge of Bayesian Statistical Methods;
- Proficient in R, specifically working knowledge of the R-STAN package for Bayesian Modelling;
- Proficient in SQL and basic database administration;
- Working knowledge of Survey statistics, sampling, and survey methods;
- Currently enrolled having completed at least two years of undergraduate studies or have recently graduated in the last six months with a BA or MA;
- Course attendance in the past twelve months;
- Proficiency in Windows, MS Office (Word, Excel, PowerPoint, Publisher, Outlook);
- Fluency in English.
Desirable Requirements:
- Graduate-level coursework in Bayesian Statistics and Survey Statistics. Public Health experience or experience with such data-sets will be an advantage;
- Some prior experience with food-security analysis or other public-health domains will be an advantage;
- Knowledge of French will be advantage.