Alumnus Kelvin ’14 on leveraging data science for stronger decision-making in Africa

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In early 2015, floods in Malawi displaced thousands of people and saw about a third of the country a disaster zone. Malawian reliance on subsistence farming also meant that the floods created a food crisis for millions across the country. To support the government of Malawi’s effort to better prepare for and prevent such flooding in the future, Zindi Africa in partnership with UNICEF and ARM, invited data scientists across Africa to interpret and generate insights from the 2015 flooding’s data.

From Accra, alumnus Kelvin Wellington ’14 was one of the data scientists across Africa that joined the call. His eventual submission, selected as the second-best by jury members from UNICEF, ARM and Zindi, was presented to the Malawian government to support policymaking and planning.

 

 

“It’s good to know the work you do can have far-reaching impact, especially at a national level,” Kelvin shared. “I am glad organisations and countries are learning to use and integrate data science in decision-making.”

Helping organisations leverage data science in decisions has become an exciting role for Kelvin. Currently working as a member of Stanbic Bank Ghana’s Enterprise Data Office, he and his colleagues are helping the bank’s leadership make strategic decisions backed by Machine Learning and Artificial Intelligence. During his time with the bank, he has helped build products for customers that provide intelligent insights into spending, and also created an application to monitor banking hall efficiency to improve queue management and client experiences, among others.

“I have always been excited about how emerging technologies impact various sectors worldwide,” Kelvin shared. “Learning about how data and data analytics space was growing, I almost immediately got immersed after Ashesi and started a career in the space. In my current role in the Enterprise Data Office at Stanbic, I work with my colleagues to help improve our customers’ overall experience with data and support data-backed decision-making. Ultimately, our goal is to help position the bank to better meet our customer needs.”

 

 

Data science, a relatively new field blending statistics, computer science, math and other subject matter expertise, is becoming recognised as a key tool for solving several challenges across Africa. In 2019, Ashesi led a conference in partnership with Data Science Africa (DSA), that brought over a hundred researchers together to discuss ways to increase the impact of data science on the continent.

“In Africa, several questions in areas such as healthcare, agriculture and disaster response would benefit greatly if domain experts were exposed to data science techniques and tools,” shared Charles Isah Saidu, Program Chair for DSA. “We must do good end-to-end data science; going to the field, collecting data using various means and technologies, and then applying machine learning techniques to build good problem-solving models.”

For Kelvin, who is one of the relatively few data science professionals in Ghana, working in the industry has provided several lessons that prove that the field does present unique opportunities for problem-solving. Key to becoming a data scientist, for him, has been the ability to keeping learning and combining seemingly unrelated areas of knowledge.

“Before joining Stanbic, for example, I had minimal finance experience and, for the most part, preferred it that way,” he shared. “At Ashesi, like many of my computer science classmates, we considered our finance classes a ‘distraction’, mostly focusing on improving our skills in technology. However, my work at Stanbic Bank requires me to draw on knowledge in finance in ways I could not have predicted when I was a student.

And as many Ashesi alumni always share once we formally begin our careers, I have come to appreciate the value of learning broadly and being able to connect knowledge from multiple fields – which is a central philosophy at Ashesi. It will be helpful for more organisations, especially universities, to focus on data science skills and learning as a critical pillar. It holds immense promise, and I believe if Ghana deepens its Data Science expertise, the country would be significantly better for it.

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