Data Scientist

Data Scientist Client: Agency of the United Nations Location: Nearshore, availability in CET working hours Duration: 60 days initial contract (extendable based on performance) Start Date: January 2026 Rate: Based on experience and Budget availability For a United Nations Agency in Geneva and to perform on remote, DropaCode is currently looking for a Data Scientist to analyse large datasets in different ways to facilitate the development of an operational definition of ultra-processed foods for regulatory and policy-making purposes. Our client is developing an operational definition of ultra-processed foods for regulatory and policy-making purposes. The overall approach is to identify a minimal set of ingredients that will with high certainty identify foods and beverages as ultra-processed using the Nova classification framework as a reference. This product will complement a guideline on consumption of ultra-processed foods being developed concurrently. The work of developing and operational definition requires the analysis of large datasets of food and beverage products from many different countries. After the data is cleaned and data variables identified, compiled and categorized, a number and variety of analyses will need to be conducted in order to identify minimal sets of ingredients. The plan is to use computer scripts to supplement human input for some tasks and largely or completely automate others. Some analyses will need to be run and rerun using different input variables. You should be responsible for: • Cleaning of the data to flag missing or incorrect data and product entries, standardize units, and ensure correct sub-categorization of products. • Generate a deduplicated master list of variables, the datapoints with which to be grouped based on function or other predefined characteristics (this may be facilitated by AI in that the information for most if not all of the datapoints in terms of which group they belong in, many be found online). • Run several analyses checking a large dataset against several predefined datapoints individually and in patterns. • Run several analyses in which de novo patterns of datapoints are identified in reference to a large datases. • Set of several computer scripts that can be run by novice R or Python users. As a Data Scientist for United Nations, you need the following: • Extensive expertise in assessing food composition datasets, employing the Nova classification framework, and extensive knowledge of the food supply in their respective country and/or region. • Experience in data management.