Women in Data Science

Featuring Harriet Kasidi Mugera, Economist and Data scientist (World Bank)

My name is Harriet Mugera. I am a young, energetic, female African Economist and data scientist. I work in the Survey Unit in the Development Data Group of the World Bank, and serve as the World Bank’s representative on the CGIAR Platform for Big Data in Agriculture’s https://ld4d.org/livestock community of practice, LD4D. My main research interests include poverty, labor, migration, agriculture and rural development. I have a particular interest and passion for agriculture as I come from a farming family in the Kenyan rift valley highlands. As a member of the Living Standards Measurement Study team, I am expert in survey instrument development, field operations, data quality control and analysis of household and agricultural survey data.

How did you come to pursue a career in data science?

My journey as a data scientist started end of 2009 by chance. I completed my Masters in Finance and tried to enter the job market. Unfortunately, for me, no financial institution was willing to hire given the Financial crisis that had hit most of Europe and the United States. Taking my Masters Supervisor’s advise, I applied for an opening as an economist and data scientist at the Food and Agricultural Organization of the United Nations in Rome. I got the job given my strong analytical and quantitative skills. I started analyzing food commodity data on and agro-systems in developing countries. This experience completely changed my life and carrier trajectory. I found my job to be very interesting and so intense so I decided to pursue my Ph.D. in Economics and continued to do research on this theme. I joined the World Bank after completing my Ph.D. and I have continued to be very passionate about data science.

What are the things you love about your role as a data scientist?

There are a lot of things I love about my role as a data scientist. The three main ones are: first, my role as a data scientist enables me to analyze data and propose concrete solutions that are evidence-based for effective decision making especially by policymakers and this in turn can affect the welfare of entire communities. Second, my role as a data scientist opens opportunities to work with different global and local stakeholders thus build synergies and work together on how to better use data for decisions. Finally, I get the opportunity to share the knowledge I have through the different outputs we produce after analyzing data.

What has been the most exciting project you have worked on, or the one you are the most proud of?

The most exciting project I recently worked on was on Livestock data in our LSMS surveys and the objective of this work was to increase the quantity and quality of livestock data available to decision makers. After examining the data, we normally collect through our household surveys and building on the experiences shared by our national counterparts in Niger, Uganda, and Tanzania, we joined forces with FAO, National Statistical Offices, ILRI and AU-IBAR to develop a livestock module template for household surveys. It was very exciting and fruitful as we engaged different stakeholders from the technical counterparts as well as the decision and policymakers in the livestock sector.

Do you feel this is an exciting time to be a woman working in the data sector?

Yes, I do feel that this is an exciting time to be a woman working in the data sector and particularly in the agricultural sector given the critical role women play in the agricultural sector. This is thanks to the availability of data that has rendered most of the research in agriculture evidence-based and thus more credible and visible.

Why do you think there is a lack of women in Tech/Data sectors?

I think that there is lack of women in the Tech/Data sectors as these have been sectors that in the past, were male-dominated. This stereotype might be a reason discouraging many women from taking this carrier path option. Moreover, many women, especially in Africa and other developing parts of the world, do not have access to information regarding opportunities in this carrier sector.

As a woman, did you face any obstacles/challenges in your career pathway to become a data scientist?

Yes, I do. I think this is inevitable in any carrier path that one takes. One of the challenges I face is what I call “the first impression” when I meet and have to work with new male colleagues. There aren’t many black African women data scientists out there today and so my presence often sparks a reaction of almost disbelief.

Any advantages in the course of your career because of your gender?

None so far.

Why should more women get into data science?

I think that more women should get into data science as they are as capable as men and thus they should be given the opportunity to participate and positively contribute to this sector.

How could more women working in data, specifically for the development/agriculture sector benefit the sector/?

I think more women working in data, specifically for the development/agricultural sector can benefit both the agricultural and development sector as women remain key in agriculture in most societies, especially in Africa, and have a greater incentive to use the data to inform policy and improve the livelihoods of other women practicing agriculture.

What advice would you give to women wanting to get into data science?

For women wanting to get into data science, I would advise them to go for it. Seize any opportunity that comes their way. Not to be intimidated by the environment and to work very hard and to give their best.