Education

B.Tech, Mathematics & Statistics | Federal University of Technology, Minna, Niger (Oct 2014 - Oct 2019)

Work Experience

Python(Bot) Engineer @ Mobi Automation (March 2022 - Nov 2023)

• Built functional bots with Python.
• Developed AI chatbots for customer service and other use cases.
• Expertise in machine learning, deep learning, and natural language processing to enhance bots.
• Maximized MySQL/NoSQL databases, API development, and data analytics for data collection, preprocessing, automation, and visualization.

Data-Science Instructor @ Click-On Kaduna Fellowship (September 2023 - November 2023)

• The Click-On Kaduna Data Science Fellowship Programme is part of the joint Kaduna State and Bill and Melinda Gates Foundation Grant for the implementation of the Data Lab Project, aimed at;
• supporting the operationalization of the State Data Revolution Plan.
• The programme seeks to equip young people with skills in Data Science.
• The Click-On Kaduna Data Science Fellowship Programme is part of the joint Kaduna State and Bill and Melinda Gates Foundation Grant for the implementation of the Data Lab Project,
• aimed at supporting the operationalization of the State Data Revolution Plan.
• The programme seeks to equip young people with skills in Data Science.

Mentee @ KaggleX BIPOC Mentorship Program (San Francisco, California) (August 2023 - November 2023)

• The KaggleX BIPOC Mentorship Program Cohort 3(formerly known as the BIPOC Grant Program).
• The goal of this program is to increase representation, create career opportunities, and develop individual growth for BIPOC (Black, Indigenous, People of Color) people in the data science industry.
• This will be achieved through pairing early-career Kagglers with advanced and senior-level mentors, curating a space for career-related discussion and learning opportunities.

Junior Associate Engineer (Data Science) @ Social Lender (Lagos, Nigeria) (March 2023 - August 2023)

• Responsible for developing and testing software apps in Python, integrating data science models.
• Collected, cleaned, and processed large data sets using Python and SQL.
• Analyzed data, created predictive models, and visualizations to inform business decisions.

Python Team Lead @ Bincom Dev Center (Lagos, Nigeria) (March 2022 - June 2023)

• Effectively coordinated team activities.
• Properly managed, assigned, and ensured quick delivery of tasks.
• Managed projects at a granular level.
• Monitored progress and growth of every team member.
• Ensured the best use of technology within the team, especially new technologies.

Python Developer Intern @ Bincom Dev Center (Lagos, Nigeria) (Feb 2022 - Mar 2022)

• Assisted the team in design, development, programming, deployment, project documentation, and other tasks during various client projects.
• Worked in teams to develop applications, including HTML and Python.
• Researched, learned, and used technology, including open-source solutions and online communities.

Skills

• Programming Languages: Python, SQL
• Libraries/Frameworks: Django, Flask, FastAPI, Selenium, Pandas, Numpy, Matplotlib, Seaborn, Plotly-dash, Microsoft Excel, PowerQuery, PowerBI, QlikView, Scikit-learn, Tensorflow, Keras, Pytouch, MLops, CI/CD, OpenAI, Langchain, TelegramBot, RASA.
• Tools/Platforms: Dialog Flow, CCAI, Odoo, AWS (EC2, Lambda, RDS, Cloud9, S3-bucket, API gateway),Git, Github, Gitlab, Azure, Docker, CircleCI, Microsoft Suite (Teams, SharePoint, Outlook, PowerPoint)
• Databases: MySQL, PostgreSQL, MongoDB, ORM

Projects

Data Analysis (YouTube Case Study)

YouTube case study using Python, Pandas, Numpy, Plotly, NLTK, Matplotlib, Seaborn, and Wordcloud. The project involved advanced text data analysis techniques, sentiment analysis to gauge audience reactions, exploration of the relationship between dislikes and views, and scrutiny of trending video tags to identify influential themes. The project's findings informed content strategies and provided invaluable insights into the dynamic ecosystem of YouTube.

• Conducted a comprehensive YouTube case study employing advanced data analysis techniques.
• Utilized sentiment analysis to measure audience reactions to videos, enhancing content strategies.
• Explored the relationship between dislikes and views, providing insights into their impact.
• Scrutinized trending video tags to identify influential and emerging themes on the platform.
• Delivered actionable insights that inform content strategies and enrich YouTube's dynamic ecosystem.

Book Recommendation

Developed a sophisticated content-based recommendation system for books using Python, Scikit-learn, Pandas, Numpy, and NLTK. This project significantly improved the user experience by delivering personalized book recommendations based on users' preferences and analyzing textual features, including authors, titles, and publishers. It employed vectorization techniques and cosine similarity measurements for efficient similarity calculations, aligning book suggestions with user interests.

• Analyzed textual features (authors, titles, publishers) to provide personalized book recommendations.
• Converted text data into numerical vectors using CountVectorizer, enabling efficient similarity calculations.
• Measured similarity between vectors to identify books with shared characteristics, ensuring precise alignment with user preferences.

Machine Learning Forecasting for Perrin Freres Champagne Sales

Perrin Freres' champagne sales forecasts. By implementing sophisticated ARIMA (AutoRegressive Integrated Moving Average) and SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous variables) models, it significantly improved the accuracy of monthly sales predictions. The insights gained from this initiative provide valuable guidance for strategic decisions, enabling Perrin Freres to adapt marketing and inventory strategies more effectively and fostering continuous growth and improvement.

• The project's improved forecasting models result in more accurate sales predictions, reducing uncertainty and enabling more precise decision-making.
• Perrin Freres can adapt marketing and inventory strategies with greater precision, leading to improved resource allocation and inventory management.
• By utilizing data-driven insights, the organization gains a competitive edge in the champagne market, enhancing its position and market share.
• The project fosters continuous growth and improvement by aligning business strategies with reliable sales predictions, ultimately contributing to the company's long-term success.

Time Series Stock Sales Forecasting

comprehensive analysis of stock price time series data. By conducting exploratory data analysis and applying advanced statistical techniques, it identified crucial stock price trends and seasonality patterns. The insights generated from this analysis serve as a foundation for developing effective investment strategies and making informed decisions in the financial market.

• Enhanced Decision-Making: The insights derived from this project provide organizations and investors with valuable information for optimizing their investment strategies.
• Risk Mitigation: By identifying trends and seasonality patterns, organizations can proactively manage and mitigate risks associated with stock investments.
• Informed decision-making based on the project's findings can lead to improved financial performance and higher returns on investments.
• Utilizing data-driven insights sets organizations apart in the competitive financial landscape, giving them a unique advantage.
• Utilized rolling statistics, seasonal decomposition, and time series forecasting.
• Identified stock price trends and seasonality patterns to provide insights for potential investment strategies.

Fake News Classifier

Developed a machine learning system for the identification of fake news articles, leveraging advanced Natural Language Processing (NLP) techniques and text classification algorithms. This project significantly improved the credibility of information sources and provided a valuable tool for identifying potentially misleading news.

• Implemented NLTK for thorough text cleansing and preparation, enhancing the reliability of news sources.
• Utilized TF-IDF for advanced feature extraction, improving the model's ability to differentiate real news from fake news.
• Developed and evaluated a Multinomial Naive Bayes classifier for news article classification, achieving impressive accuracy and efficiency.
• Integrated the powerful Passive Aggressive Classifier, enabling the model to adapt dynamically to evolving news content while maintaining high classification accuracy.
• Employed a confusion matrix to measure classification performance, including accuracy, precision, recall, and F1 score, ensuring a high standard of reliability.

Support AI (Conversational Chatbot)

Developed a versatile cross-platform support bot that seamlessly integrates across websites, social media, and messaging apps. This innovative solution is empowered by natural language understanding (NLU) for human-like interactions and leverages the OpenAI API to deliver intelligent and personalized responses. It serves as a 24/7 support assistant, instantly resolving common queries while remaining cost-efficient, data-driven, and easy to integrate into existing systems.

• Seamlessly integrates across websites, social media, and messaging apps, ensuring a consistent and unified support experience.
• Utilizes advanced Natural Language Understanding (NLU) for human-like interactions, enhancing user engagement and satisfaction.
• Empowered by the OpenAI API, enabling the delivery of intelligent and personalized responses to user queries.
• Provides instant resolution of common queries, offering round-the-clock support and improving user experience.
• Delivers a cost-efficient solution that leverages data-driven insights and is easily integrated into existing systems for streamlined implementation.

Scan Verify Access (SVA) Bot

The Access Control bot seamlessly integrated blockchain-based verification within Telegram interactions, creating a pioneering solution that harmoniously merges the robust security of decentralized ledger technology with the user-friendly interface of a widely adopted messaging platform.

• Developed a blockchain-powered Telegram bot for investor verification.
• Ensured wallet authenticity and ownership for secure group access.
• Effectively mitigated the risk of fraudulent activities and scams.
• Seamlessly integrated blockchain verification into Telegram interactions.
• Empowered group administrators to maintain trust and integrity.
• Streamlined investor onboarding for a user-friendly experience.
• Enhanced organization's reputation and trustworthiness.

Talks & Lectures

• Empowering Nigeria's Youth: Harnessing the Power of Blockchain and Artificial Intelligence for Employment - Seminar Digital Onboarders(NYSC), 2023
• Recommender Systems - Office session Nexascale Data Science Community, 2023
• Unleashing your tech potential: (A journey of Growth & Success) - Twitter Space, 2023
• Data Analysis With Natural Language Processing - Bincom Dev center knowledge development session, 2022
• Exploring Artificial Neural Networks - Bincom Dev center External event, 2022
• Data Visualization for improved Business Insights - Bincom Dev center knowledge development session, 2022
• Data Privacy For Increased Customer Data Protection - Bincom Dev center External event, 2022
• Best websites to learn code 2021 - Medium Article, 2021

Certifications

• Mobile Web Specialist - Google Developers
• Tunga Data Structure and Algorithms - Tunga
• Intermediate Machine Learning - Kaggle