The Center for Effective Global Action (CEGA) at UC Berkeley

ATAI Data Scientist (Postdoc)


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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. We are seeking outstanding applicants for a Postdoctoral researcher (Postdoc) to support the Agricultural Technology Adoption Initiative (ATAI).

Please note: This position will also be posted without the PhD requirement, upon approvals from UC Berkeley central systems (forthcoming). For this reason, we ask applicants that did not receive a PhD in the last five years to still consider submitting application materials for consideration if they are interested in the position and meet all other requirements.

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. 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, ATAI requires all full-scale RCTs collect information on program costs for the interventions being evaluated. This requirement came into effect in June 2015, and currently all active studies are collecting this information.

Scope of Work

In 2018, ATAI launched renewed activities to generate learning across its portfolio of field experiments. As part of these efforts, we will mobilize a Postdoc around a series of activities to examine ATAI data resources, identify and advance opportunities for meta-analysis, and propel findings into the public domain.

This position will be full-time, and is funded through December 2022, with a preferred start date by May 2019.

Specific tasks include the following:

Aggregation, analysis, and display of existing data resources: Over the past eight years, ATAI has supported nearly 50 randomized evaluations in 17 different countries across Sub-Saharan African and South Asia. The Postdoc will aggregate these resources as part of a new “ATAI dataverse,” working collaboratively with J-PAL’s knowledge management and data quality team to build and maintain the portal. As data is brought together, the Postdoc will collaborate with ATAI’s faculty directors to identify ways to link this information in a manner that allows for meta-analysis and maximum cross-study comparability. The Postdoc will then support analysis, suggesting hypotheses, performing analytics, and reporting findings. 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) should be fully explored and implemented where possible. The ATAI Postdoc will similarly work with J-PAL’s knowledge management and data quality team to specifically assess the program’s costing data, organizing and presenting this information in a manner that ultimately allows ATAI to compare across interventions and potentially project cost-effectiveness for replications and scale-ups of programs tested elsewhere.

Advise and support new data collection efforts: ATAI is preparing to launch a new “diagnostic” funding window to encourage researchers to collect information on areas where good descriptive data is lacking. In the immediate term, diagnostic data collection exercises will be oriented toward gender equity, nutrition, food security, and longer-term indicators of economic diversification, agroindustry, value addition, and mechanization. The goals of this mechanism include building foundational knowledge that opens new avenues of inquiry, harmonizing data collection across studies, generating hypotheses, and offering insights for program and policy planners. The ATAI Postdoc will support the program’s faculty directors in making recommendations of where valuable diagnostic data could be collected, the mechanisms by which to do so, and then analyze this information to inform policy and research questions.

The position will work with guidance from ATAI’s Board Officers Craig McIntosh (UC San Diego), Tavneet Suri (MIT), and Jeremy Magruder (UC Berkeley) and with direct support from members of the ATAI Secretariat. We advise you do not contact these faculty members directly, as they will only redirect you to the formal application process below.

Core Responsibilities:

Work closely with faculty leaders and staff from ATAI to develop a robust data analytics research agenda for the program

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);

Work with faculty leaders to suggest key hypotheses to test using ATAI data and other data sources;

Perform data analytics and report hypotheses, summary statistics, and findings to ATAI faculty in a clear, logical, and reproducible manner;

Develop visualizations, summary statistics, and presentations, which use ATAI data inform policy and research communities on the advancement of smallholder agriculture;

Identify datasets that can be linked with ATAI survey data, perform linkages, and display results;

Collaborate with J-PAL’s knowledge management and data quality team to assess and implement options for cost effectiveness analysis across the ATAI portfolio;

Develop and manage the ATAI dataverse, 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;

Review ATAI funding applications, assessing opportunities for additional “diagnostic” data collection exercises, advising faculty directors, and proposing data collection methods;

Serve as resource for ATAI on survey questions, modules, and data collection strategies for ATAI’s new “transformation metrics”;

Understand and adhere to ATAI’s policies and protocols regarding data security and confidentiality.

Required Qualifications Completed a PhD* within the last five years in economics, social sciences, public policy, mathematics, statistics, or related field. Training in microeconomics, econometrics, and statistics is required.

3‐5 years 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;

3‐5 years 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 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 and data science can be used to create valuable global public goods;

Familiarity with randomized controlled trials;

Experience working in developing countries (preferably in a research-related capacity);

Experience cleaning, labelled, and documenting datasets for public repositories;

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 Scientist Postdoc” Submittable page:

Please note: This position will also be posted without the PhD requirement, upon approvals from UC Berkeley central systems (forthcoming). For this reason, we ask applicants that did not receive a PhD in the last five years to still consider submitting application materials for consideration if they are interested in the position and meet all other requirements.

Applications will be reviewed on a rolling basis until the position is filled.

Time commitment: Not specified

  • Category Global Poverty
  • Created by Jeanette Aguilar
  • Submitted 05 Feb
  • Last updated 05 Feb