By Adam Keally
I have been working at Kimetrica as an Applied Research and Modeling Intern for almost 5 months now. Kimetrica is a social enterprise committed to delivering impact by increasing the effectiveness of spending in the social sector. They provide software, research, survey, and modelling and impact simulation services for evidence-based decision-making and learning. Kimetrica works with governments and non-profit organizations to increase the impact and efficiency of their social investments, enhance accountability, manage critical risks, and build donor or taxpayer confidence.
I sought out an internship with Kimetrica to further my quantitative and programming skills. I support two projects through research, data wrangling and cleaning, and economic modeling. The literature reviews include compiling and summarizing relevant findings, as well as extracting estimated parameters to incorporate in project models. The data work is primarily done in Python and I have a great team supporting me as I pick up new skills in this area, such as data manipulation, visualization, and mapping within Python. I have learned a great deal about managing large amounts of data and the infrastructure required for an effective organization.
Most of my work at Kimetrica has been split between two projects that reflect different my professional interests. The first is the Food Security Third Party Monitoring (FSTPM) project which provides critical, near real-time analysis to support targeting of life-saving support. This allows USAID and its partners to make highly-informed, evidence-based decisions for program implementation and strategy, which improves the impact of USAID’s critical humanitarian assistance.
The second project sits within the World Modelers group at Kimetrica, which is developing parameterized quantitative models that generate output variables for population, conflict, household economics, water, markets, health, and humanitarian operational response that impact food security. The end goal is for these models to evolve into a web-based tool that key actors in the field can interact with to support their decision-making process. The models will support temporal and spatial prediction of pre-defined indicators so that clients can explore scenarios and compare interventions.
This internship has been an incredible opportunity to gain exposure to data science and applied economics in the international development and humanitarian operations field. I have been surrounded by a supportive and knowledgeable team with diverse backgrounds, making it a great workplace. I am grateful for the past 5 months and I will continue to make the most of this experience.