Fisayo Nathaniel

I am a results-driven Backend and Machine Learning Engineer with extensive experience designing and building scalable solutions using C#, Python, ASP.NET Core, .NET, ML.NET, and Azure Cloud services. Over the years, I have contributed to mission-critical projects across healthcare, fintech, and commerce media, consistently delivering optimized, high-performance applications that solve real-world problems.

On the backend engineering side, I specialize in architecting distributed SaaS systems, developing APIs, integrating third-party services, and ensuring robust data pipelines. My expertise spans the full software development lifecycle (SDLC) from solution design and coding to debugging, deployment, and post-release optimization. I am particularly passionate about performance tuning and have refactored existing APIs to improve speed, scalability, and reliability.

On the machine learning side, I leverage ML.NET, AutoML, and LightGBM to build predictive models, recommendation systems, and intelligent services. I’ve implemented regression, classification, and recommendation algorithms for real-world use cases such as drug quantity prediction in healthcare, recommender systems for better decision-making, and transaction reliability models for fintech. Beyond prototyping, I focus on deploying ML solutions as production-ready APIs and integrating them seamlessly into business workflows.

Notable projects include:

• Healthcare Systems: Contributed to platforms like eRx (consultation payments for medical professionals) and HealthSend (diaspora-driven health insurance funding in Nigeria).
• ML for Healthcare: Designed models to ensure accurate drug dispensation for HMOs and improve reliability in health services.
• Fintech Reliability: Explored ML-driven approaches with NIBSS to prevent failed transactions and enhance customer trust.
• Commerce Media: At Kindred (UK), worked on ad optimization platforms that transformed how ads are bought and delivered.

I bring a unique blend of deep backend engineering expertise and applied ML problem-solving, allowing me to bridge the gap between traditional software systems and intelligent, data-driven solutions. My career goal is to continue developing scalable, AI-powered backend systems particularly in healthcare and financial technology while contributing to global innovations that improve people’s lives