About the role
Responsibilities Improve and extend analytical method templates for residence location inference from MNO data Support technical conversations with mobile network operators on data needs and designs Assess inferable information from each operator's data, geography and targeted area Write method specifications and validation criteria for operator data engineers Guide operator engineering teams through implementation and run in-country workshops Design for privacy by minimizing data shared, using aggregation and privacy-enhancing technologies Build internal training material on strengths and limits of MNO data Requirements Strong mathematical modeling, machine learning and statistics Deep comfort with spatio-temporal data, GIS and sparse, irregular observations Ability to reason without ground truth and set parameters from data shape Pragmatic trade-off between accuracy and implementability Excellent communication with engineers, leadership and non-technical colleagues Experience writing technical specifications others implemented Able to read and review SQL and Python Commitment to privacy by design and confidentiality Preferred Qualifications Experience with Call Detail Records or latching data Experience with mobility, transport, sensor or remote-sensing data Familiarity with privacy-enhancing technologies such as private set intersection or homomorphic encryption Poverty modeling, survey data or mobile network operator experience Comfort travelling to fragile and post-disaster contexts Benefits Base salary and bonus at target performance, plus an annual benefits stipend About the Company GiveDirectly delivers cash directly to people living in poverty and crisis across 15 countries. It is a fast-growing organization with rigorous impact evaluation.