Top (Kaggle) Ranked Data Scientist, Microsoft MVP Award-winning AI Developer and certified Azure AI Engineer with deep expertise in Microsoft tools, machine learning, and C#.NET MAUI development. Proven ability to design and deploy advanced AI solutions, drive data-driven decision-making, and lead complex projects from concept to deployment. Eager to leverage a strong background in predictive modeling, data visualization, and scalable software development to exceed organizational goals in a competitive environment.
Work
Brainydaps Tech LTD
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Founder / Managing Director
Remote, Intercontinental
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Summary
Founder and Managing Director at Brainydaps Technology Limited, a fully remote Data Science and Artificial Intelligence Company registered in Nigeria.
Highlights
Leadership: Leading various teams in different departments of the company through example setting, empathy, communication, and role modeling, while building company culture.
Management: Coordinating activities of teams by assigning tasks and deadlines on the project management tool ClickUp.
Executive Functions: Handling legal registration, incorporation, and creating a corporate bank account.
Operational Strategy: Assigning executive roles to experts for the creation of legal agreements, scope of work, Standard Operating Procedures, Customer Journey Maps, and service catalogs.
HA-SHEM Limited
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Training Officer (Artificial Intelligence & Machine Learning)
Lagos, Nigeria
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Summary
AI & ML Trainer delivering comprehensive corporate training, material development, and professional learner mentorship.
Highlights
Curriculum Development: Design and develop comprehensive training curricula in AI and ML aligned with organizational learning objectives.
Material Development: Create professional presentation slides, learning resources, and instructional materials for instructor-led training.
Corporate Training: Deliver engaging corporate training programs in AI and ML with a focus on practical applications.
Learning Coordination: Plan and coordinate classroom exercises, hands-on activities, and collaborative sessions.
Assessment & Evaluation: Design and administer assignments, quizzes, and assessments to evaluate trainee progress.
Learner Support & Mentorship: Guide trainees on effective study strategies and mentor them on career development in AI/ML.
FlowDevs
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Data Scientist Contractor
Remote, Minnesota, USA
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Summary
Working as an independent Contractor on an Ad Hoc basis.
Highlights
Webinar Hosting: Host and coordinate webinars on topics such as Data Science and AI.
Market Optimization: Run reinforcement learning algorithms on market data to increase the efficiency and impact of marketing efforts.
Business Strategies: Involved in key business strategy areas including pricing techniques, website presentation, and social media engagements.
Spiritual Data
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Data Scientist
New York, New York, USA
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Part Time
Summary
Contributed to AI model development and quality assurance at Spiritual Data through data labeling, source code testing, and collaborative improvements.
Highlights
Selected and accurately labeled data points within the database, crucial for grounding and enhancing the retrieval augmented generation (RAG) model.
Performed rigorous source code debugging and field testing of compiled code, ensuring software quality and performance.
Contributed actively to team collaboration platforms (Notion, Discord), providing actionable suggestions for product and process improvements.
Data Scientists Network
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Data Scientist
Lekki-Ajah, Lagos, Nigeria
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Seasonal
Summary
Applied expertise in machine learning and software development to enhance community engagement, mentor junior data scientists, and deliver external data science solutions.
Highlights
Leveraged machine learning, Python scripting, C#.NET MAUI software development, and data visualization/wrangling expertise to successfully deliver diverse data science projects.
Delivered data-driven solutions for external clients, applying advanced data analysis, visualization, and modeling to solve complex business problems.
Mentored junior data scientists, guiding them through project development, data analysis, and ML techniques, fostering their growth and ensuring code quality through regular reviews.
Coordinated and hosted data science webinars featuring industry experts, managing all logistics, marketing, and technical aspects to ensure successful execution and knowledge dissemination.
Contributed to the strategic growth of the Data Scientists Network community, fostering member connections and shaping organizational direction through active participation in strategic planning.
Emlaj Group
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Data Scientist
Lekki, Lagos, Nigeria
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Contract
Summary
Led data science initiatives at Emlaj Group, delivering actionable insights, predictive models, and robust data pipelines to drive business growth and optimize resource allocation.
Highlights
Developed and deployed interactive Tableau dashboards and reports, generating actionable insights into sales trends, customer behavior, and market dynamics that informed data-driven decision-making across the organization.
Engineered and deployed machine learning models (regression, clustering, time series) to accurately predict property prices, sales volumes, and crop yields, optimizing resource allocation and driving business growth.
Designed and implemented robust data pipelines, integrating disparate sources (property listings, customer databases, weather APIs) to ensure data quality, consistency, and scalability for advanced analytics.
Executed clustering analysis to segment high-value customer segments, directly informing targeted marketing campaigns that boosted revenue growth and customer loyalty.
Created and maintained comprehensive BI reports and dashboards, providing stakeholders with real-time KPI insights that facilitated data-driven strategic decisions.
Volunteer
Live Moderator
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Microsoft Build 2026
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Served as a Live Moderator for the Microsoft Developer channel on YouTube, answering both technical and non-technical questions from a global audience.
Highlights
Moderated the live chat, removing inappropriate comments and keeping the environment friendly and fun.
Virtual Mentor (Fellow)
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Microsoft Copilot & Agentic AI Summit
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Mentored winning teams at the virtual Microsoft Copilot & Agentic AI Summit, engaging with over 30,000 participants from EMEA.
Highlights
Mentored winning teams, coordinated activities, and answered questions for over 30,000 participants at the Microsoft Copilot & Agentic AI Summit.
Contributed to the development of emerging AI talent by providing guidance and support to teams in a high-profile virtual summit.
AMA Expert at Azure AI Booth
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Agentcon Lagos
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Served as an Ask Me Anything (AMA) Expert at the Azure AI Booth during AgentCon Lagos, contributing to the global AI community.
Highlights
Provided expert guidance and answered questions at the Azure AI Booth, supporting attendees at a major global AI community event.
Webinar Host
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Data Scientists Network (DSN)
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Hosted a 4-part series of live webinars titled 'Machine Learning Made Simple' under the DSN umbrella, introducing ML concepts to all expertise levels.
Highlights
Covered supervised/unsupervised learning, classification, regression, reinforcement learning, and preprocessing pipelines.
Demonstrated the AI Calculator project to show traditional ML power.
Uploaded recordings to YouTube playlist: https://youtube.com/playlist?list=PLclzo-BGGtKXMjL52xw5bUMPIvmJLD55b
Education
Indiana University
Indianapolis, Indiana, USA
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MScApplied Data Science
Imo State University
Owerri, Imo, Nigeria
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BScComputer ScienceGrade: 4.0/5.0
Starfield College
Agege, Lagos, Nigeria
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High School DiplomaHigh School DiplomaGrade: 5 A1, 1 B2, 2 B3
Awards
Guinness World Records Holder
Guinness World Records
Achieved record for participating in the 'most users to take an online Multi-level artificial intelligence lesson in 24 hours', highlighting global engagement in AI education.
Microsoft MVP (Most Valuable Professional) Award
Microsoft
Recognized for significant contributions in Development Tools (.NET Category), demonstrating exceptional technical expertise and community impact.
LinkedIn Community Top Data Science Voice Q4
LinkedIn
Recognized as a Top 5% voice in the LinkedIn Data Science community for Q4 2024, indicating significant influence and thought leadership.
LinkedIn Community Top Data Mining Voice Q4
LinkedIn
Recognized as a Top 5% voice in the LinkedIn Data Mining community for Q4 2024, highlighting expertise and engagement in data mining discussions.
GitHub Stats
GitHub
Achieved 130+ Stars and 1500+ followers on GitHub, reflecting strong open-source contributions and community recognition for technical projects.
Top 0.5% Data Scientist on Kaggle (Dataset Category)
Kaggle
Ranked among the top 0.5% globally out of 14,000 data scientists in the Dataset category, showcasing excellence in data curation and feature engineering.
Top 0.3% Data Scientist on Kaggle (Notebook Category)
Kaggle
Ranked among the top 0.3% globally out of 59,000 data scientists in the Notebook category, demonstrating superior analytical and modeling skills.
Languages
English
Fluent
Yoruba
Conversational
French
Basic
Certificates
Python
Sololearn
Artificial Intelligence A-Z Build 7 AI
Udemy
IRB Members
CITI Program
Social/Behavioral Researchers
CITI Program
C# Intermediate
Sololearn
SQL Intermediate
Sololearn
Machine Learning A-Z AI Python
Udemy
Data Science A-Z Hands On
Udemy
Research Security Training
CITI Program
Social and Behavioral Responsible Conduct of Research
CITI Program
Microsoft Azure AI Engineer Associate
Microsoft
Skills
Data Science & Machine Learning
Machine Learning, Python Scripting, Data Visualization, Data Mining, Data Wrangling, Predictive Modeling, Forecasting, Clustering Analysis, Customer Segmentation, Business Intelligence, KPI Monitoring, Sentiment Analysis, Text Classification, Hyperparameter Tuning, AutoML, ML.NET, LightGBM, SQL, Excel, Gretl, Tableau, MSVS SSDT (SSIS, SSAS, SSRS).
Artificial Intelligence & NLP
AI Engineering, Natural Language Processing (NLP), Retrieval Augmented Generation (RAG), Multi-agent Systems, AI-powered Recommendations.
Software Development & Platforms
C#, .NET MAUI, C#.NET MAUI Software Development, XAML, Mobile Development (iOS, Android, MacOS, Windows), Shell MVVM Architecture, GitHub, Debugging, Field Testing, Code Reviews, Scalable Architecture, UI/UX Design.
Projects
AI Calculator - Intelligent AI-Powered Calculator Application
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Summary
An intelligent AI-powered calculator application with multi-platform compatibility and advanced mathematical functions.
Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET, LightGBM, AutoML
Developed an intelligent AI calculator application using .NET MAUI, enabling the app to run seamlessly across iOS, Android, MacOS, and Windows, ensuring consistent performance and user experience on all platforms.
Implemented machine learning models for basic arithmetic operations: Stochastic Dual Coordinate Ascent (SDCA) for addition and subtraction, and LightGBM for multiplication and division, enhancing accuracy and performance for mathematical calculations.
Designed a flexible architecture using .NET MAUI and ML.NET, which allowed each arithmetic operation to be handled by its own dedicated machine learning model, ensuring modularity and ease of future expansion.
Utilized the AutoML functionality within ML.NET to automatically fine-tune the model hyperparameters, optimizing training accuracy and reducing the manual tuning effort for each machine learning model.
Developed a dynamic ModelCall class to handle the logic of selecting and applying the appropriate machine learning model for each operation, providing a seamless integration of ML models with the user interface built using .NET MAUI.
Trained separate machine learning models using seperate datasets for building seperate model of the different arithmetic operations, ensuring reliable performance for a variety of user inputs, and adapting to edge cases for both simple and complex calculations.
Optimized performance by incorporating LightGBM for efficient, high-speed multiplication and division operations, ensuring that the app could handle large datasets and complex calculations in real-time.
Integrated trigonometric functions (sine, cosine, and tangent) and power/root functions to broaden the app’s capabilities, offering a wide range of mathematical operations beyond basic arithmetic.
Delivered a smooth, cross-platform user experience by developing the front-end interface using XAML in .NET MAUI, ensuring the app was intuitive, responsive, and visually appealing across all supported platforms.
Tested the application thoroughly, performing real-world usability tests and ensuring all mathematical operations and machine learning models provided accurate results across various devices and input scenarios.
Barbara - Multi-Agentic AI Application
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Summary
A multi-platform AI application for mental health insights, leveraging smart device data and AI models.
Platform: iOS, Android, MacOS, Windows
Framework: .NET MAUI (Shell MVVM Architecture)
Hackathon Submission: 2025 Microsoft AI Skill Fest (Winners to be announced)
Developed a multiplatform AI application using .NET MAUI, ensuring compatibility across iOS, Android, MacOS, and Windows platforms while maintaining consistent user experience through Shell MVVM architecture.
Integrated data from smart devices (i.e smart watch) to gather user-specific health metrics, allowing the application to provide highly personalized mental health insights based on both journal entries and health data.
Designed and implemented an intelligent multi-agent system that mimics a well-read psychologist and data analyst, processing and analyzing users' journal entries and health metrics to provide actionable recommendations.
Collaborated with cross-functional teams to create a seamless journal app integration, allowing users to record daily reflections and provide mental health insights that are both data-driven and psychologically sound.
Participated in the 2025 Microsoft AI Skill Fest Hackathon, submitting the project as a proof of concept for AI-driven mental health improvement, while keeping the codebase optimized and scalable for future development.
Established an intuitive user interface using XAML and C# , with a focus on accessibility and ease of use, enabling users to track their mood, mental health progress, and receive motivational prompts.
Trained AI models using ML.NET to analyze textual and numerical data from users, delivering actionable insights based on sentiment analysis and health condition trends, aiming to reduce pandemic-related depression symptoms.
Talking Stage - Multi-Platform QnA AI Application
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Summary
A multi-platform QnA AI application for automating romantic relationships question answering, utilizing NLP and ML.NET.
Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET, LightGBM
Developed a multi-platform QnA AI application using .NET MAUI framework, enabling the app to run seamlessly across iOS, Android, MacOS, and Windows, ensuring consistent functionality and design on all devices.
Leveraged NLP techniques from the ML.NET framework to process and understand natural language queries from users, allowing the AI to engage in meaningful, context-aware conversations during the "talking stage" of romantic relationships.
Integrated LightGBM's multiclass classification algorithm for text classification, enabling the app to predict and match user queries with predefined responses based on the most accurate classification of the user input.
Engineered a machine learning prediction engine that intelligently matches user queries to a predefined dictionary of responses, offering users a personalized, AI-driven experience while reducing the burden of repetitive conversations.
Designed and implemented a dynamic response system using machine learning models to handle varied user inputs and provide tailored responses, thus improving the user experience during the early stages of romantic conversations.
Optimized the performance of the application by incorporating efficient data processing pipelines for real-time NLP query analysis, significantly reducing response times and enhancing the app’s responsiveness.
Collaborated with cross-functional teams to refine the user interface and experience, ensuring the application was both intuitive and engaging for users seeking a conversational AI to assist with the "talking stage" in relationships.
Achieved a seamless user experience through XAML to craft an intuitive and accessible UI, enabling users to interact easily with the app without technical hurdles, and making sure the app could scale as new features were added.
Bumble Formula - Classification AI Application
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Summary
A classification-based AI application for predicting user behavior on dating apps.
Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET
Developed a classification-based AI application using ML.NET and .NET MAUI, enabling a multiplatform solution for predicting user behavior on dating apps such as Bumble, Tinder, and Badoo, providing insights into trends and patterns of Nigerian women.
Utilized the AutoML toolkit from ML.NET for hyperparameter tuning, optimizing the classification model to accurately predict a variety of behaviors based on publicly available profile data, ensuring improved prediction accuracy for different user profiles.
Designed and implemented a custom classification model to identify behavioral patterns and trends in users' profiles, offering data-driven insights that could assist men in navigating the online dating environment more effectively.
Maintained rigorous data privacy standards by anonymizing personally identifiable information (PII) and ensuring compliance with the Nigeria Data Protection Regulation (NDPR), adhering to best practices for ethical data use and protection.
Trained and tested the machine learning models using diverse datasets, ensuring the model could handle a range of behaviors and responses while remaining focused on ethical use, with no sensitive or personally identifiable data being processed.
Leveraged ML.NET’s classification algorithms and feature selection techniques to ensure that the model could categorize user behavior accurately, improving the ability to predict and understand user preferences based on their public dating profiles.
Presented findings and insights from the project in a clear, accessible format, demonstrating the potential for machine learning to assist in customer segmentation and enhance decision-making processes in a business or social context.
Explored the potential for future development by creating a roadmap for automating behavior classification and streamlining the online dating experience, with the long-term goal of helping users find better matches more efficiently through AI-powered recommendations.