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Data Analytics, Visualization & Website Design at IFMR Lead
Posted by Misha Sharma (@mishasharma)
ifmr lead https://hasjob.co/ifmr.ac.in/gg971 , Chennai · ifmrlead.org · Short-term contractShort-term contract · ProgrammingProgramming
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 policy makers 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: IMFR LEAD supports policy debates with empirical data and analysis, and provides further insight to policy-makers 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 and 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.
Job Description:
IFMR LEAD currently seeks a qualified 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/data visualization and software applications. Components of the job profile are mentioned below:
Web Development & Dashboard Design
Creation of a data portal/ dashboard for the KGFS Study database that provides access to the project metadata, surveys completed and that are currently on-going. The website will also be data intensive and will be used as a platform to present relevant data and analysis through graphics, interactive maps and charts. Initially the website will be for internal use, and will later be made available for public access.
Data Visualization
The project will involve getting familiar with primary datasets on the study (in stata format) and brainstorming on ways in which the data can be presented visually on the website. To start with, the pilot phase will involve putting together summary statistics and basic profiling of the data. On the household level, it could involve presenting data about the socio-economic characteristics of the households, their income and expenditure profile, credit and savings patterns, status of their access to financial services, etc. The data can also be presented at the village/block/district level across a set of indicators. The exact variables that are of interest for data visualization would be identified shortly through discussion with the KGFS team.
Data Modelling
The study is conducted in partnership with IFMR Rural Channels, a private financial institution that rolls out rural bank branches (KGFS) to increase access to financial services for people living in rural and remote areas. Understanding the socio-economic characteristics of their clients, and factors that motivate them to take up a KGFS product would be immensely beneficial to the KGFS bank branches so as to strategically design their products and bring innovation in their services. Simultaneous use of customer management database (CMS) provided by KGFS and the primary data collected by our research team would help us in extracting key information about the KGFS clients and understanding their motivation to join KGFS. The dataset can also be used to analyse factors related to higher success of some branches, i.e., why some branches are doing better than others.
Project Description:
Together with our partner organization KGFS (KshetriyaGrameen 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 RohiniPande from Harvard University and Erica Field from Duke University.
Basic Qualifications:
• 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 Bachelor’s/Master’s degree in Computer Sciences are preferred.
• Proven analytical skills, including, specifically, skills working with quantitative data using econometric methods
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