CEGA’s Digital Credit Observatory (DCO) invites proposals for small grants of up to $50,000 each (including indirect costs) to support new survey modules, new treatment arms, descriptive studies, and/or pilots of new gender-focused interventions that help us answer important questions related to digital credit (understood to mean mobile phone-based loans that are instant, automated, and remote) and women’s economic empowerment:
- How do digital credit products and related lending practices economically empower–and disempower–women?
- How can the design of digital credit products and related lending practices be optimized to promote financial inclusion and economic empowerment for women?
Please read carefully through the application guidelines and direct any questions to our staff team at email@example.com
Data Scientist (Postdoc)
The Center for Effective Global Action (CEGA) is a hub for research on global development, with a network of nearly 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).
Agricultural Technology Adoption Initiative
Co-implemented by the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT and CEGA, 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.
Postdoc 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.
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.
- 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.
- Completed a PhD in economics, social sciences, public policy, mathematics, statistics, or related fields. 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;
- 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.
How to Apply
Please upload brief cover letter, CV and contact information for two academic references to the "ATAI Data Scientist Postdoc" Submittable page: https://cega.submittable.com/submit/131396/atai-data-scientist-postdoc
Applications will be reviewed on a rolling basis until the position is filled.
BITSS will hold its next Research Transparency and Reproducibility Training (RT2) in Washington DC, September 11-13, 2019. This RT2 is organized in partnership with the World Bank’s Development Impact Evaluation (DIME) group.
RT2 provides participants with an overview of tools and best practices for transparent and reproducible social science research. The curriculum is developed and delivered by academic leaders in the open science movement and there is space for collaborative work and hands-on skill building. Participants are encouraged to bring their own research questions and ideas to seek support and feedback from instructors and other attendees. Learn more about previous RT2 events here.
RT2 curriculum focuses on the following topics:
- Ethics and Mertonian norms for research transparency and reproducibility
- Scientific misconduct and researcher degrees of freedom
- Improved specification through study pre-registration and pre-analysis plans
- Computational reproducibility and approaches to replication
- Techniques for reproducible meta-analysis
- Hands-on practice with version control using Git (GitHub or the Command Line)
- Dynamic documents with R and Stata
- Data management and de-identification for data sharing
- Appropriate use of statistics and interpretation of statistical evidence
RT2 is designed for researchers in the social and health sciences, with particular emphasis on economics, political science, psychology, and public health. Participants are typically (i) current Masters and PhD students, (ii) postdocs, (iii) junior faculty, (iv) research staff, (v) librarians and data stewards, and (vi) journal editors, funders, and research managers curious about the implications of transparency and reproducibility for their work.
RT2 curriculum is most applicable to research that uses quantitative or mixed methods. Applicants should have proficiency in R or Stata.
Fees and Financial Support
Tuition for RT2 is $1,500 for three days, including breakfast, lunch, and a networking reception on September 13. This tuition fee does not cover costs for travel and accommodation.
Financial Support: For up to 30 participants, BITSS offers partial or full financial support by waiving the tuition fee and covering travel, lodging and child care. Financial support will be awarded based on a combination of merit and need, taking into account our commitment to facilitate access to RT2 for diverse and underserved populations.
Submit an application using the form below. The application includes questions regarding (i) your motivation for participating in RT2 and (ii) how you expect your participation to contribute to scaling-up education and training on research transparency and reproducibility.
Applications should also include a Curriculum Vitae or Resume. Letters of Reference are also accepted, though they are not required. Please submit these as attachments in the online application portal.
BITSS aims to select no more than 40 participants for RT2. With this in mind, the number of applications for RT2 tends to exceed the number of available spaces.
BITSS staff will lead the selection process with oversight from the BITSS Faculty Director. Competitive selection will be based on the (i) quality of application materials and expected impact and (ii) balance across disciplines, gender, and institutions.
Applications from self-funded participants will be considered on a rolling basis. Self-funded applicants will be assessed based on the same eligibility criteria as those requesting financial support.
To be considered for financial support, applications must be submitted no later than 11:59 pm PT June 2, 2019. Notifications of acceptance for applicants with financial support will be sent no later than June 14, 2019.
BITSS will consider applications for self-funded participants on a rolling basis through 11:59 pm PT August 28, 2019.
Reach out to BITSS Senior Program Associate Aleksandar Bogdanoski (firstname.lastname@example.org) with any questions about RT2 DC.