Ingabire is a statistician by training with experience in data analysis, data visualization, and training. She is wrapping up two years as a Data Quality Analyst and we talked to her to hear about her background and her experience at Laterite.
Ingabire, you are Rwandan, but you studied in South Africa. How did you end up in Pretoria? And why did you choose Statistics as a major?
I grew up in South Africa. At the time the University of Pretoria was ranked 5th best University on the continent, I had to try and get in there, which I did.
I had a passion for Biology and Mathematics and I chose to go with numbers because I knew this would open many opportunities for me in the future. As an undergraduate, I had an opportunity to work for Standard Bank in the Corporate and Investment Banking division where I instantly grew a healthy fascination for Statistics. There was something about creating tables of numbers and being able to analyze and create stories out of those numbers that made sense to me and this is how I ended up majoring in Statistics and Economics.
What brought you back to Rwanda and to Laterite?
I had planned my return home to be at the age of 30 mainly to build my father’s tombstone. It was important to come home to a stable job that embodied my values and those of my father’s. He stood for development, and for majority’s gain rather than individual gain, I stand for authenticity and self-identity. Laterite satisfies all those career values for me, as an organization we tick all the boxes. Working for an organization that impact policies on the reduction of child malnutrition, gender-based violence and shows how interventions have positive effects on our communities, all of this evidenced by reliable data, was the dream job.
Why is data important?
Data helps us gather information for human development. This is important in many fields, from marketing to stock-trading. In development research, data can, for example, identify which agricultural methodology enhancements are useful, or spot the trends in high school dropouts, or highlight underage malnutrition prevalence within specific age brackets.
What is the work of the Data Quality Team?
Our team is responsible for ensuring the quality of the data we deliver to clients. Without being too technical the team codes surveys, monitors the incoming data to allow real-time feedback and corrections. We also processes and clean the data to deliver a de-identified, organized, ordered and fully translated dataset as the end product.
I work to improve our internal processes and data quality. An exciting function of my role is that of developing systems and tools that are efficient, effective and automated to consistently improve our quality control and monitoring of our collected data.
What skills do you use?
I use my statistical knowledge, SPSS and STATA programming experience to accomplish most of my tasks. And I also use my ability to adapt quickly to any software that sometimes comes as a prerequisite from client’s brief specifics.
What was your favorite project at Laterite?
I enjoyed all projects I have done at Laterite, but a favorite would definitely be a project funded by the World Bank aimed at reducing stunting and malnutrition in children aged 5 and below. This was the biggest data collection project that Laterite has done to date, and to ensure our data quality we had to use Inter Rater Reliability to assess our collected information. We did this by comparing responses and gauging if respondents were understanding questions the same, and also if enumerators were taking correct anthropometric measurements. This helped us improve our data collection methodologies whilst data collection was still undergoing, a first for me in the 7 years of data analysis experience I have had.
This goes to show you that indeed at Laterite we do not just go by the book, we are counter disciplinary and so are always ready to employ new age techniques to improve on the work we do.