Amarachi Nnanyelu

I’m a health data scientist with a B.Sc. in Applied Biochemistry and a growing career at the intersection of healthcare, data science, artificial intelligence, and research. My background gives me both a strong understanding of biological and health-related problems and the technical skills to analyze data and build technology-driven solutions.

My professional and project experience spans data analytics, public health, research, project coordination, and AI. I have worked with public health teams supporting maternal, newborn and child health activities, integrated measles-rubella and polio campaigns, and Emergency Operations Centre activities. These experiences strengthened my understanding of how health systems operate in real-world settings and how data can support decision-making.

On the technical side, I work with Python, SQL, R, Excel, Power BI, Tableau, Streamlit, GitHub, and data workflows and automation tools. I have experience with data cleaning, analysis, visualization, exploratory analysis, and machine learning, and I enjoy turning messy or complex datasets into useful insights. I have also explored APIs, workflow automation with tools such as n8n and Make, and AI-powered applications.

My research interests focus particularly on chronic disease management, preventive healthcare, health informatics, bioinformatics, AI for early disease detection, digital health, and responsible use of health data. I’m interested in combining information from sources such as electronic health records, wearable devices, genomics, and environmental data to develop more proactive approaches to healthcare.

I have also built and explored projects involving chronic disease prediction, stroke risk prediction, health analytics, food and nutrition recommendations, and AI-enabled preventive healthcare. I enjoy projects that sit between technical development and real-world impact, particularly where data science can improve health outcomes or make complex systems more efficient.

Beyond technical work, I enjoy research, science communication, problem-solving, and learning new technologies. I’m especially interested in remote opportunities in data science, data analytics, health technology, AI, research, operations, and related roles where I can contribute analytically while continuing to grow technically.

I’m motivated by work that combines rigorous analysis with meaningful impact, and I’m particularly excited by teams building useful products, improving decision-making through data, or applying AI thoughtfully to real-world problems.