👋 Hello There, I'm Mkhanyisi!

Backend Development

I wield a diverse skill set spanning various languages and frameworks for Web servers and other types of task automation as well. Beyond server-side applications, I’ve scripted functions for various tasks that consume different libraries or API integrations including third parties, and managed data persistence across SQL and NoSQL databases. My deployment proficiency extends to AWS cloud services, as well as Docker containerization with exposed REST endpoints.

I approach problems methodically, adhering to best practices and design patterns to ensure robust scalability and performance. Experienced in API integration and crafting bespoke solutions expanding functionality, including writing controller functions, and leveraging third-party services. I’ve contributed to both monolithic( including MVC) and microservice architectures, including serverless deployments.

My capabilities encompass optimizing data structures, service calls, and database operations while prioritizing security best practices.

Frontend Development

I am proficient in developing intuitive and visually appealing user interfaces, bringing the intended aesthetic and responsiveness of a page to life. I have collaborated closely with designers and product stakeholders to translate mockups and wireframes into polished front-end implementations that align with the intended user experience on the client side.

With a strong foundation in vanilla HTML, CSS, and JavaScript, I have also honed my skills and worked using in modern front-end frameworks such as React.js. My expertise extends to creating responsive designs that deliver exceptional user experiences across various devices and screen sizes. Additionally, I possess a keen eye for detail and a commitment to optimizing performance and accessibility standards to ensure that front-end applications are both efficient and inclusive.

Machine Learning

My strong academic coursework and practical projects have equipped me with a strong foundation in statistical machine learning, deep learning, and data analysis. I have extensive experience across the ML development lifecycle from data extraction, cleaning, and feature engineering to model training, evaluation, and integration.

I’ve applied both statistical and deep learning methods to real-world problems, particularly in time series forecasting, regression analysis, and diagnostic reporting. My work has supported product improvement and R&D initiatives, with predictive insights often delivered directly to business stakeholders, including C-suite audiences.

I’ve contributed to internal tools where trained models were integrated into analytics workflows, improving the accuracy, reliability, and interpretability of product-facing metrics. I prioritize business-aligned evaluation, practical model fit, and clear visual communication to cross-functional teams.

I'm continually intrigued by data-driven approaches to problem solving both within the business context and beyond, including Applied Machine Learning/Gen AI solutions. I bring a full-stack mindset and take strong ownership of integrating machine learning solutions into tools that drive measurable impact.