My Pivot Journal is a Ventures Africa weekly series documenting people’s career transitions from one industry to another, especially to tech.
Wuraola Oyewusi is keen on enjoying herself in all she does. And this is one of the reasons she transitioned from pharmacy to data science. Now she is a data scientist, AI researcher, and technical instructor. As icing on the cake, she teaches tech hacks in her native language – Yoruba.
How it started
Oyewusi is a graduate of Clinical pharmacy from Olabisi Onabanjo University, Ogun State. After pharmacy school, she kick-started her career with a professional internship at the National orthopaedic hospital in Lagos state. Afterwards, she worked as a pharmacist at e-health Africa in Kano. During this period, she was actively involved in many things including patient counselling, inventory control and management, and provision of comprehensive pharmaceutical services to people living with HIV/AIDS. She also dispensed and verified drug prescriptions.
For Oyewusi, finding out about tech was purely by chance. Tech was not part of the options she envisaged she could explore career-wise. But being open-minded often influenced her into reading random job roles and descriptions. On one of such spontaneous searches, she saw a job role for a data analyst.
As a person with robust experience willing to take up challenges, she felt she could do everything on the list except for Structured Query Language (SQL). “So I decided to check what that was. That was how I got into tech,” she narrated.
Oyewusi began learning in earnest. Since her background was in health, she was alien to the data analytics field. Hence, she had to do a lot of knowledge immersion. After finding out about SQL in the job requirement, she took courses and gradually learnt there were data languages one needed to write to get exact data. “The better you are at phrasing your terminology’s bad language, the better you can get the data out,” she said.
For Oyewusi, it is imperative that whoever wants to go into the data science field needs to conceive a picture of what data science is and then work on understanding conversations. She explained, “Understanding conversations makes you realise your learning is coming together. It helps you to understand what you do not know yet and what you know already.”
She emphasises that the internet is largely generous, and people often have learning options. And this is quite beneficial because it gives the learner a chance to switch to a preferred instructor. Importantly, she argues that one of the main concepts of brilliant learning is to build on what you know.
“Some people studied programming in school, so it will be nice if they start from python for data science as their entry. For example, I was learning things like linear algebra from scratch. People who studied mathematics have always known that. So they can start with the mathematics of machine learning. It is possible a nutritionist will do a good job of understanding data related to nutrition and food. You should consider data science techniques as tools that are not mysterious. Rather they help you improve your work,” she explained.
Building on her background, Oyewusi works with clinical data. “You will understand that because I work in the health sector, I have worked with that type of data almost all my career, not from the data science perspective. Typically, when you are learning a new field, you have to look at where you are coming from, maybe what you studied in school,” she said.
Casual learning for her is not an efficient way to learn and thrive in a new industry. While there is no industry standard time for learning, she spent four hours every day for three months during the learning process. However, she does not see the learning process as challenging. “I am exploring a new field, and there are requirements to be great at it, so it is not a challenge to me,” she noted.
How it’s going
Interestingly, Oyewusi also teaches data science and evolving tech concepts in Yoruba. This has grabbed the attention of several people on Twitter and Linkedin who find it exceptional and beneficial to native speakers of the language who are tech enthusiasts. When asked how she started tech exposition in her native language, she explained, “I did it just because I can. I speak Yoruba a lot and have had a robust knowledge of technical concepts for a long time. I knew people would watch because they read many of my articles. As a pharmacist, I have some experience working with older people, and I have tweeted about how people would bring their grandparents and wait to talk to me. I have a way of communicating with people like this who may not be as fancy because they are curious.”
Oyewusi has a couple of honours to her name. She was recognized as a UK Global Talent in AI, Machine Learning, and Data Science. She was also among the 80 African women advancing artificial intelligence in Africa and the world, and also Top 100 Women in Tech in 2020 as a Nigerian Female Leader in Artificial Intelligence for Development. She is also the author of Hands-On Natural Language Processing, an AI course on LinkedIn Learning.
Well, this is what Oyewusi has always wanted, “The goal was to be great at data science, and I have done quite some interesting work that has entertained my soul. I subscribe to the philosophy of enjoying where you are on the way to where you are going. I have enjoyed every phase of my career. It is not like I know what I will be doing this time next year, but the only thing that is constant is that I will be enjoying myself in all I do,” she said.
Deliberate practice, and patience.
“I am one of those who go the extra mile when learning a technique and can engage with things up to 200 times, just to know what is wrong. I will try again and learn again. I am not in a hurry. I am kind to myself. When things fail, I do not go hard on myself. Many things fail,” she said.