Start date: As soon as possible
IFMR LEAD, headquartered in Chennai, India, is a young, fast-growing organization focused on improving access to financial services for the poor through cutting-edge research, knowledge dissemination and outreach to policymakers and practitioners. IFMR LEAD’s strategy is to use rigorous, empirical research to:
- Inform practice: Through research, IFMR LEAD provides evidence on what works and what does not.
- Inform policy: IFMR LEAD supports policy debates with empirical data and analysis, and provides further insight to policymakers from its field experience
Towards this goal, IFMR LEAD aims to facilitate a process where research questions emerge from the local policy context and policy and programmatic decisions are guided by research outcomes.
Evidence for Policy Design (EPoD) at the Center for International Development at Harvard University is a research initiative that promotes the use of rigorous evidence to improve design and implementation of public policies to enable efficient service delivery and sustainable economic development. Current research topics at EPoD include governance, education, entrepreneurship, health, agriculture, sustainable development, and access to finance. Geographically, our research covers South Asia, Indonesia, Africa, Latin America, and the U.S., and we draw from a network of expert academics with expertise in various topics and regions.
The Development Lab at Duke University is a research program that employs scientific techniques in the rigorous evaluation of policy and the training of tomorrow’s thought leaders in development economics. We inform public policy by working alongside policymakers to design and test interventions that will maximize the reach of public resources and more effectively deliver services to the poor. Current research topics at the Development lab include access to finance, maternal health, nutrition, labor markets, transportation, and agriculture. Geographically, our research covers South Asia, Mongolia, and parts of Africa and Latin America.
EPoD and the Development Lab have partnered with IFMR LEAD to implement a number of large-scale field research projects and policy engagements in India that address urgent topics related to economic development and public policy.
IFMR LEAD currently seeks a qualified data engineer/data scientist to provide support on data analytics initiatives of the KGFS project. The candidate will work from Chennai, with close supervision from the Data Analytics Lead at Harvard, to perform data cleaning and analysis, manage databases, and produce graphics and software applications. In addition, the candidate will be involved with the production of policy-related op-eds and data journalism-style pieces.
Together with our partner organization KGFS (Kshetriya Grameen Financial Services), a rural financial services provider in Tamil Nadu, this study aims to achieve an in-depth understanding of the impact of using rural bank branches to provide comprehensive financial services. The intervention at the heart of this study provides a unique opportunity to undertake a rigorous experimental evaluation of the impacts of bank branch expansion in rural areas at both the household and village level. Using a randomized controlled trial we evaluate a financial service delivery model that uses bank branches in villages to provide a full range of credit, savings, and insurance services to entire communities. This study is led by Rohini Pande from Harvard University and Erica Field from Duke University.
- Minimum experience of 2 years performing statistical analysis;
- Extensive experience with a statistical analysis package such as R, Python (pandas, scikitlearn), or Stata;
- Minimum experience of 2 years programming with Python;
- Minimum experience of 2 years with an open source web development stack preferred;
- Experience working with a cloud database service such as AWS;
- Experience using version control software (git);
- Candidates with Master’s degree are preferred;
- Solid understanding of research project design and processes;
- Proven analytical skills, including, specifically, skills working with quantitative data using econometric methods.
Send your resume, cover letter, and a writing sample to firstname.lastname@example.org. In the subject line, please write exactly your first (given) name, last (family) name, as well as the text “Data Scientist - IFMR LEAD”. Applicants will be reviewed on a rolling basis. You will benefit by submitting as early as possible. Only short-listed candidates will be contacted for an interview.
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