Interview with Share Adebodun Adeleye: A Leading Data Scientist
Share Adebodun Adeleye is a prominent data scientist whose expertise bridges finance, healthcare, and artificial intelligence. Her career is driven by a commitment to translate data insights into meaningful outcomes—whether influencing decisions in boardrooms or enhancing patient care in hospitals. From predictive models that improve customer engagement at Leadway Pensure to analytics that support public health interventions, Adeleye brings exceptional breadth and depth to data science.
What sets your work apart from others in the field?
My work stands out because of its cross-sector application. While many data scientists specialize in a single industry, I’ve applied advanced analytics and machine learning across finance, customer intelligence, and healthcare. My goal has always been clear: to move beyond insight and create transformation. Data science should improve processes, anticipate behaviour, and support critical interventions.
Can you share some highlights of your contributions at Leadway Pensure?
At Leadway Pensure, I led initiatives that modernized decision-making through data. I developed real-time KPI dashboards, predictive models for customer retention, and anomaly detection systems to optimize asset portfolios. These tools helped identify clients likely to churn, enabling proactive engagement strategies. The result was improved service quality and a stronger culture of data-driven leadership across the company.
What motivated your shift into healthcare analytics?
The motivation was simple: to use data to save lives. I saw that analytical tools used in finance could also predict clinical outcomes. For example, I built a heart attack risk prediction model with 84.6% accuracy, integrating patient demographics, lifestyle, and vital signs to aid early intervention. Since then, I’ve developed models for mental health and substance use prediction—areas where data science can enhance care and inform policy.
What does being one of the few women in this field mean to you?
It’s both humbling and inspiring. Women are significantly underrepresented in senior data science and AI roles, especially those spanning diverse sectors like finance and healthcare. I am proud to be among the African women leading in technical, high-impact areas. My aim is to redefine possibilities for future generations of women and girls in STEM.
Can you talk about some of the systems you’ve engineered?
I designed and implemented the Bay Area Rapid Transit (BART) SQL database system to support large-scale analytics. It was built for speed, data integrity, and scalability by optimizing schema design and query logic. This enabled faster access to critical data and more efficient reporting. I have also developed ensemble machine learning models for housing price prediction and decision support tools for executives. Across sectors, my systems combine technical strength with practical impact.
Could you tell us more about your education and training?
My academic background laid the foundation for my career. I earned a Bachelor of Science in Computer Science from Oduduwa University, graduating with honours and focusing on software engineering and systems architecture. I then completed a Master’s degree in Computer Science at San Francisco Bay University, specializing in machine learning, AI, and data engineering. Alongside formal education, I pursued certifications in predictive analytics, AI, and big data platforms to stay current in a fast-moving field.
What’s next for you, and what do you envision for the future of data science in Nigeria?
I plan to deepen my work in health analytics and focus on mentoring emerging data scientists, especially women. Nigeria has immense talent, but it needs the right infrastructure and opportunities to thrive. Data science will be critical for advancing healthcare, resource management, urban planning, and governance. I want to contribute both as a leader and collaborator to this progress.
What fuels your passion?
Purpose drives everything I do. Every model and insight must answer one question: “Will this improve someone’s life?” Whether helping financial clients get better service or enabling early clinical risk detection, data science’s ultimate role is to serve people. This belief guides my work and defines my career.
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