I'm a senior full stack engineer across AI and traditional software domains. I have extensive experience in both B2B and B2C SaaS product development. I've led projects from concept to deployment, including data management and curation tools, search platforms powered by knowledge graphs, recommendation engines, and AI-powered web applications using modern tools.
<EXPERIENCE/>
{> Senior Full Stack SWE
Kallikor
At Kallikor, I'm currently working on advanced AI-powered simulation tools that transform complex real-world environments into digital representations. This enables businesses to visualize, analyze, and experiment with their operations using digital twins and enterprise metaverses.
{> Senior Full Stack SWE
Nossa Data
As part of the first engineering hires at Nossa Data, I played a pivotal role in developing the ESG reporting and data management platform. I was instrumental in advancing the product from its initial MVP to its current state, contributing significantly to its architecture and feature set.
{> Engineering Lead
PhilanthroLab
At PhilanthroLab, I led the development of the Social Safety Net, a comprehensive search engine for social services and social good. This involved creating an extensive knowledge graph optimized for machine learning to deliver precise results and assist individuals in need.
{> Software Engineer
Datopian
At Datopian, I was a key individual contributor in the development of PortalJS (https://github.com/datopian/portaljs), a modern JavaScript framework designed for rapidly building rich data portals. I focused on enhancing the framework's capabilities, ensuring seamless integration with various backends, including CKAN, to provide customizable and interactive data presentation solutions.
{> Machine Learning Engineer
Data Science Nigeria
At Data Science Nigeria, I worked as a Machine learning engineer and Researcher, working on end-to-end data analytics projects encompassing data collection, exploration, transformation, modeling, and deriving actionable business insights.
<SKILLS/>
> Here are my technical skills and areas of expertise:
> Technical Stack
> Domain Expertise
<PROJECTS/>
2D Animation Editor - Create simple 2D animations with ease from your browser, no need to install any software. This intuitive browser-based editor lets you create frame-by-frame animations, add keyframes, and export your work in various formats. Perfect for creating animated GIFs, short videos, and simple motion graphics.
Interior Design Editor - Create your dream interior design with our easy-to-use editor. Fully browser-based, no need to download or install anything. Features an intuitive drag-and-drop interface, real-time preview of all changes, and access to a comprehensive library of architecture assets to help bring your vision to life.
A comprehensive audience engagement platform that helps creators and businesses grow, engage, and monetize their audience through customizable link screens, analytics, and email marketing tools.
A versatile collection of utilities including random generators (numbers, colors, countries, etc.) and data structure manipulation tools (JSON formatter, CSV converter, Markdown editor). Built to simplify common development tasks.
<RESEARCH PAPERS/>
> Optimizing Health Facilities Allocation for COVID-19 Management Using Social Vulnerability Index and Spatial Data Analysis
This study recognises that building new health centers would be slow and expensive in preparation for the pandemic and as such uses social vulnerability index, demographic and environmental statistics to propose suitable existing centers that needs to be re-equipped.
Read Paper >> DataSist: A Python-based library for easy data analysis, visualization and modeling
This paper presents a new python-based library, DataSist, which offers high level, intuitive and easy to use functions, and methods that helps data scientists/analyst to quickly analyze, mine and visualize big data sets
Read Paper >> Predicting Bank Loan Default with Extreme Gradient Boosting
This paper provides an effective basis for loan credit approval in order to identify risky customers from a large number of loan applications using predictive modeling.
Read Paper ><TALKS/>
<BLOGS/>
> How to put machine learning models into production
An opinion piece curating best guide in putting machine learning models in production
Read Article >> How to Serve Machine Learning Models with TensorFlow Serving and Docker
Learn how efficiently serve machine learning models with Tensorflow serving
Read Article >> Deep Dive into ML Models in Production Using Tensorflow Extended (TFX) and Kubeflow
An end-to-end tutorial that shows you how to deploy, scale and monitor deep learning models with Tensorflow Extended and Kubeflow on GCP
Read Article >> Build, Train, and Deploy a Book Recommender System Using Keras, TensorFlow.js, Node.js, and Firebase
An end-to-end tutorial that explains how to train, save, and deploy a recommender system
Read Article ><CONNECT/>
> echo "Let's connect!. Here's how you can reach me:"
> echo "I'm always open to interesting conversations and collaborations!"