Center for Effective Global Action (CEGA) is Hiring a Data Analyst PhD Student — 6/30/2019 Published: June 6, 2019 By: Andy Sohn The Center for Effective Global Action (CEGA) is a hub for research on global development, with a network of over 100 academic researchers extending across the University of California, Stanford University, and the University of Washington. Our faculty affiliates design and test solutions for the problems of poverty, generating actionable evidence for policy-makers in less developed countries. Using rigorous field trials, behavioral experiments, and tools from data science, we measure and maximize the impacts of economic development programs throughout the world. CEGA is seeking outstanding PhD student applicants to support the Agricultural Technology Adoption Initiative (ATAI), based at either UC Berkeley, or UC San Diego. Agricultural Technology Adoption Initiative Co-implemented by CEGA and the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT, ATAI generates data and insights needed to inform productive investments in agricultural development. The program is led by a consortium of leading social scientists who conduct large-scale randomized evaluations in direct partnership with implementers like the CGIAR, World Bank, international NGOs, and national ministries of agriculture. More than one hundred thousand individuals have been surveyed to date as part of ATAI evaluations. Per ATAI policies, each of these data are to be made publicly available as a resource for the global policy and research community, while ensuring that personally identifiable information is protected. Valuable information is included in these resources, including household and plot-level information on prices, production, and a variety of farmer welfare indices. In addition, since June 2015, ATAI has required all full-scale RCTs to collect information on program costs for the interventions being evaluated. This year ATAI launched renewed activities to generate learning across its portfolio of field experiments, including a mandate to better utilize the wealth of primary data collection we have commissioned. Scope of Work The PhD student hired will collate and examine publicly available ATAI datasets, identify and advance current and future opportunities for meta-analysis, and help encourage data publication. This position will be part-time (estimated 50% time, to be finalized with the selected candidate), with a start date to be set (preferred during the summer of 2019, although we will consider early start dates for fall semester/quarter of 2019). Up to 100% time may be possible if working during the summer semester/quarter. This position has the opportunity to extend, meaning that a hire who produces sufficient quantity and quality of work in the first semester could be asked to stay on in the following semester/quarter(s). The position will work for ATAI’s faculty leads Craig McIntosh (UC San Diego), Jeremy Magruder (UC Berkeley), as well as Tavneet Suri (MIT), with support from CEGA and J-PAL staff. Specific tasks include the following: Over the past eight years, ATAI has supported more than 50 studies, more than half of which are randomized evaluations in 17 different countries across Sub-Saharan African and South Asia. The PhD student will aggregate the data resources publicly available thus far. As data is brought together, the PhD student will collaborate with ATAI’s faculty leads to identify ways to link this information in a manner that allows for cross-study comparability. Opportunities to link these efforts to external resources (for example, UN FAO, the University of Washington Evans School Policy Analysis and Research Group, and the World Bank’s Living Standards Measurement Survey) will be explored and implemented where fruitful. Advise and support new data collection efforts: The PhD student will support the program’s faculty directors and staff in making recommendations of specific indicators that could be collected across contexts as a way to facilitate meta-analysis ex ante. ATAI will be commissioning a set of common indicators, as well as “diagnostic” top-up data collection exercises to encourage researchers to collect information on areas where good descriptive data is lacking and they are already headed to the field. In the immediate term, diagnostic data collection exercises could investigate gender dynamics, food security, “inclusion” across the income distribution, soil tests or environmental assessments, and/or improved agricultural input or output measurement approaches. Core Responsibilities: Become familiar with ATAI’s datasets (including fields, data types, and constraints), and the software used to view and analyze them (GIS skills strongly preferred); Collate ATAI’s datasets, collaborating with J-PAL’s knowledge management and data quality team to support regular flow of data publication, tracking project completion and compliance with data publication policies; Identify datasets that can be linked with ATAI survey data, perform linkages, and display results; Perform data analysis and report summary statistics and findings to ATAI faculty in a clear, logical, and reproducible manner. As the opportunity arises, develop visualizations, summary statistics, and presentations which use existing ATAI data to inform policy and research communities on the advancement of smallholder agriculture; Work with faculty leaders to suggest key hypotheses to test using ATAI data and other data sources; Work closely with faculty leaders and staff from ATAI to develop the foundations of a robust data analytics research agenda for the program; Collaborate with J-PAL’s knowledge management and data quality team to assess and implement options for cost effectiveness analysis across the ATAI portfolio; Serve as resource for ATAI on survey questions, modules, and data collection strategies for ATAI’s new “transformation metrics”; assess opportunities for additional “diagnostic” data collection exercises, advise faculty directors, and propose data collection methods. Understand and adhere to ATAI’s policies and protocols regarding data security and confidentiality. Required Qualifications Current PhD student at UC Berkeley or UC San Diego. Training in microeconomics, econometrics, and statistics is required. 2+ years of hands-on experience wrangling large, heterogeneous data sets, particularly demonstrating aptitude with spatial data; candidates should also demonstrate competence working with survey, administrative, and/or time series data; 2+ years of hands-on experience using GIS software as well as R, Stata, SAS, and/or Microstrategy, preferably with strong experience using Python and/or other scientific computing languages. Desired Qualifications PhD students in Economics, Agricultural & Resource Economics or similar programs are preferred. Familiarity with randomized controlled trials; Experience cleaning, labeling, and documenting datasets for public repositories; Experience working in developing countries (preferably in a research-related capacity); Experience designing, managing, and implementing different data gathering strategies, including: (i) semi-structured interviews, (ii) focus groups, and (iii) surveys; Interest in agricultural development and ways in which quantitative research can be used to create valuable global public goods; Experience developing data visualizations (using Tableau or similar platform) that are accessible to non‐academic audiences; Ability to interact with individuals at all levels in a fast‐paced environment, sometimes under pressure, while remaining flexible, proactive, tactful, resourceful and efficient, and with a high level of professionalism and confidentiality. Application Requirements Please upload brief cover letter, CV and contact information for two academic references to the “ATAI Data Analyst (PhD Student)” Submittable page. Applications will be reviewed on a rolling basis until the position is filled; deadline to apply is June 30, 2019.