Destiny Owobu

About Me

Destiny Owobu is from Edo State, Nigeria. He obtained two Bachelor's degrees in Accounting and Economics and Statistics from the University of Lagos and the University of Benin, respectively. He spent three years doing an MSc in Accounting at the University of Benin. He also holds a micro-certificate from the Corporate Finance Institute, a Canadian institution, as a Financial Modelling and Valuation Analyst. Recently, he completed an Executive MBA from Quantic School of Business and Technology in Washington DC, USA. For the past 10 years, Destiny has been employed with ProjectBrains Tutorial, a lecture house providing remedial education services in Benin City, Nigeria. He has trained and personally tutored over 8,000 students who were seeking admission into the University of their choice. As Director of Studies and Teacher he oversaw the implementation of the curricullum and taught Mathematics, Statistics and Economics. Thousands of his students have successfully gained admission to prestigious universities both inside and outside Nigeria. Destiny has also worked as an Associate Lecturer in Accounting at Wellspring University, a private university in Benin City. He possesses extensive knowledge in Business Management, Startup Entrepreneurship, and digital marketing. Recently he tried to leverage his business, accounting, statistics and finance education to pursue a career in Data Science at Sand Technologies (formerly Explore Data Science Academy)in South Africa. He completed a one-year internship with the institution as a Data Science Graduate Intern. He just completed his AICE program at the Africa Leadership Academy(ALX) to master Artificial Intelligence Skills intranet.alxswe.com/certificates/RMCrL3NcX7. He strongly advocates for education as the principal weapon for economic development, wealth creation, and effective political participation. His latest venture is the Business Crusader Academy, a business school for Small and Medium Enterprises (SMEs). Destiny helps businesses with knowledge tools to solve business problems, grow and become more profitable. He is a regular guest on local television, Independent Television Station (ITV) in Benin City, where he discusses business, economy, and political topics. He is married to Mrs. Michelle Oghobase Owobu.

Favorite quotes

"Anyone good with the hammer thinks every problem is nail".

Destiny Owobu's Portfolio

Welcome to my portfolio! Here you'll find a selection of my work showcasing my skills and expertise in the Data Science industry. Feel free to browse through the projects below to get a glimpse of what I can offer.

 Projects

Data Science Graduate Intern with Sand Technology (2014-2015) 

Here are some key highlights of what I accomplished during my time at Sand:

1. Wrote validation and inference scripts for a Low Cost Clutter model to support network infrastructure site planning.

2. Geocoded over 250,000 addresses submitted by a multinational client using open source tools OpenStreetMap and Nominatim geocoding library. This potentially saved the company $2000 based on a quotation from Google.

3. Helped populate a Data Register, aiding transparency and traceability in data sourcing and processing pipelines.

4. Explored how Large Language Models (LLMs) could augment ward-level data acquisition in Nigeria where public data is sparse.

5. Conducted a classification of Nigeria’s 774 local governments into urban, rural, and semi-urban classes using multidimensional features like population density, network infrastructure, broadband speed, building footprint, and the Relative Wealth Index (RWI). The model was 92 percent accurate in classifying the administrative boundaries.

6. Created an Opportunity Score using a rule-based technique to guide a marketing campaign Strategy for a multinational telecommunications client using features like competitor infrastructure layout, geospatial data on building density, network infrastructure, demand variables like population density, relative wealth index, industrial clusters, service gaps as shown by internet speeds. The solution was able to select 4000 buildings out of 21000 for sales targeting. 

Predictive Maintenance for Water Company: A Data Science Project

Project Team: Bonani, Banele, Dakalo ,Destiny ,Lesiba,Mkhosi, Sakhile, and Zukhanye.

My Role: Project Manager

Project Overview

As the project manager, I led a dynamic team of data scientists and data engineers in developing a predictive maintenance solution for a water company as part of my internship project at Sand Technologies. The primary objective was to develop a machine learning model to anticipate machine failures, and minimize downtime and maintenance costs, thereby improving operational efficiency.

 Key Contributions

1. Exploratory Data Analysis (EDA)

I spearheaded the Exploratory Data Analysis (EDA) phase to uncover crucial insights and patterns in the dataset. This involved:

- Cleaning and preprocessing data from various sources including telemetry, maintenance logs, failure records, and error logs.

- Conducting statistical analyses to understand the distribution and relationships between key features.

- Visualizing data trends to identify potential predictors of machine failures.

2. Model Development: Random Forest Classifier

I personally developed and fine-tuned the Random Forest model, which was selected for its robustness and accuracy in handling complex datasets. The key steps included:

- Feature Engineering: Identifying and creating features that significantly impact machine performance.

- Model Training: Training the Random Forest model on historical data to predict machine failures with high precision and recall.

- Evaluation: Achieving impressive results with an Accuracy of 99.92%, Precision of 99.90%, Recall of 99.92%, and an F1 Score of 99.91%. The model's ROC AUC score was 0.919, demonstrating its effectiveness in distinguishing between different failure modes.

 3. Presentation to Stakeholders

I successfully presented our findings and the predictive maintenance solution to an audience of investors and analysts. The presentation included:

- High-Level Overview: Summarizing the project objectives, methodology, and key milestones achieved.

- Demo: Showcasing the interactive dashboards and visualizations that illustrate early insights and model predictions.

- Remaining Work Outline: Providing a clear plan for future work, including model deployment and continuous improvement strategies.

- Retrospective: Highlighting the biggest accomplishments, challenges faced, and risk mitigation strategies for the project.

- Q&A Session: Engaging with stakeholders to answer questions and discuss potential impacts and scalability of the solution.

Project Impact

The predictive maintenance model developed by our team is set to revolutionize how the water company manages its equipment. By accurately predicting machine failures, the company can:

- Reduce Downtime: Schedule maintenance proactively to prevent unexpected failures.

- Optimize Maintenance Costs: Focus resources on machines that need attention, reducing unnecessary maintenance.

- Improve Operational Efficiency: Ensure consistent performance of critical machinery, leading to better service delivery.

 Conclusion

This project highlights my ability to lead a data science project from inception to delivery, combining technical expertise with effective communication and stakeholder management. My hands-on involvement in EDA, model development, and presentation underscores my commitment to driving data-driven solutions that deliver tangible business value.

 Portfolio Project: The Science of Bets

I am excited to share the successful completion of our SQL data analysis project, titled "The Science of Bets," which focused on the European Soccer dataset available on Kaggle. This project was undertaken as part of our intensive four-week training program on SQL queries and database management program.

Project Overview:

Our project delved into the rich dataset of European soccer matches, leveraging SQL concepts such as Joins, Unions, Query optimization, and Normalization techniques. Working within the Jupiter Notebook environment, we meticulously cleaned and modified the data to extract meaningful insights and patterns.

Key Techniques Used:

 Throughout the project, we applied advanced SQL techniques to analyze the dataset comprehensively. This included performing various Joins to merge different tables, optimizing queries for improved performance, and implementing normalization techniques to ensure data integrity and consistency.

Findings and Insights:

Our analysis yielded fascinating insights into European soccer leagues and teams. Notable findings include the Netherlands Eredivisie having the highest average of goals scored, while the France Ligue 1 League recorded the highest number of clean sheets. Additionally, teams such as Barcelona and Real Madrid emerged as dominant forces, leading in most wins, goals scored, and home turf performance.

Presentation and Visualizations:

To effectively communicate our findings, we crafted a compelling presentation featuring SQL codes/queries, graphs, charts, and tables. This presentation was shared with the general pod on October 17th, 2023, and provided a comprehensive overview of our analysis process and key insights. You can view our presentation slides here: [Link to slides](https://lnkd.in/dK3HFWXk)

Conclusion:

"The Science of Bets" project exemplifies our team's proficiency in SQL data analysis and our ability to derive actionable insights from complex datasets. By combining technical expertise with strategic analysis, we uncovered valuable insights into European soccer leagues, contributing to our broader understanding of sports analytics and data-driven decision-making.

Team Contributions:

I extend my sincere appreciation to my dedicated team members for their hard work and collaboration throughout this project. Together, we successfully navigated the intricacies of SQL analysis and delivered impactful insights.

#DataScience #SQLAnalysis #FootballInsights

 Netflix Data Analysis Portfolio Project

I'm thrilled to share the successful completion of a comprehensive Data Analysis project, undertaken as part of the Data Science Certificate program at Explore AI Academy. Collaborating with an exceptional team of students, we delved into the intricacies of Netflix data, extracting valuable insights and presenting actionable recommendations.

Project Overview:

Our project centered on analyzing Netflix data sourced from a CSV file, employing powerful data analysis libraries including Pandas, NumPy, and Matplotlib. Over a two-week period, we meticulously structured the data, performed extensive cleaning, and conducted in-depth analysis and visualization.

Methodology:

Employing a MECE (Mutually Exclusive Collectively Exhaustive) framework, we segmented the Netflix product offerings into two distinct categories: Movies and TV Shows. This allowed for a more granular analysis of user engagement and content preferences across different genres and formats. Additionally, we explored regional variations, program watch durations, and the influence of popular directors and cast members on viewer engagement.

Tools and Technologies:

To facilitate collaboration and streamline project management, we leveraged a suite of collaborative tools including Trello for task management, Discord for communication, and Github for version control and code hosting. These tools played a crucial role in ensuring seamless coordination and efficient progress tracking throughout the project lifecycle.

Findings and Recommendations:

Through our analysis, we generated insightful visualizations such as correlation matrices, line plots, pie and bar charts, and geographical distribution histograms. These visualizations provided valuable insights into user behavior and content preferences on the Netflix platform. In our final presentation, delivered via Canva slides and Google Meet, we articulated a compelling data story and presented actionable recommendations aimed at enhancing Netflix's product offerings and driving user engagement.

Conclusion:

Our Netflix Data Analysis project exemplifies our team's dedication, analytical prowess, and collaborative spirit. By harnessing the power of data and employing advanced analytical techniques, we have provided valuable insights and actionable recommendations to drive business growth and enhance user satisfaction on the Netflix platform.

Team Members:

I extend my sincere gratitude to my esteemed teammates: Priscilla, Mashoto Kgasago Mulalo, and Mathanda, as well as our Pod leader, John Mohale, for their invaluable contributions and unwavering commitment to the project's success.

#DataAnalysis #DataScience #ExploreAIAcademy

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 Waga Vacation Planning App

Introduction:

The Waga Vacation Planning App project aims to revolutionize the way individuals plan and organize their vacations. With a focus on user experience and convenience, Waga offers a comprehensive platform that integrates personalized trip recommendations, seamless booking functionalities, and real-time itinerary management. This project portfolio highlights the key achievements, milestones, and future prospects of the Waga app development.

Project Scope and Objectives:

The primary objective of the Waga project is to develop a user-friendly vacation planning app that simplifies the travel experience for users. Key components of the project include:

- Designing an intuitive and visually appealing user interface.

- Implementing algorithms for personalized trip recommendations based on user preferences and constraints.

- Integrating with popular travel booking platforms for seamless booking and itinerary management.

- Conducting thorough testing and refinement to ensure a smooth user experience across different devices and platforms.

Achievements and Milestones:

1. Initial Conceptualization and Planning:The project kicked off with extensive brainstorming sessions to define the app's core features, target audience, and competitive landscape. A detailed project plan was developed, outlining key milestones and deliverables.

2. UI/UX Design: Our design team worked diligently to create wireframes and mockups that embody the Waga brand and deliver an intuitive user experience. Feedback from user testing sessions was incorporated to refine the design further.

3. Backend Development: The development team focused on building robust backend systems to support the app's functionalities, including data processing, recommendation algorithms, and API integrations with third-party services.

4. Frontend Implementation:Concurrently, frontend developers brought the designs to life, ensuring responsiveness and accessibility across various devices and screen sizes.

5. Integration and Testing: The app underwent rigorous testing to identify and address any bugs or performance issues. Integration with external APIs for booking and itinerary management was seamlessly executed.

6. Launch and User Feedback:The Waga app was successfully launched on app stores, garnering positive feedback from early adopters. User engagement metrics and feedback were continuously monitored to inform future updates and enhancements.

Future Prospects and Enhancements:

Moving forward, the Waga team is committed to ongoing improvements and feature enhancements to enrich the user experience. Key areas of focus include:

- Further refining recommendation algorithms to provide more accurate and personalized trip suggestions.

- Expanding integration with additional travel booking platforms to offer users more choices and flexibility.

- Enhancing social sharing and collaboration features to facilitate group trip planning.

- Exploring opportunities for localization and expansion into new markets to reach a wider audience of travelers.

Conclusion:

The Waga Vacation Planning App project represents a significant milestone in the travel and tourism industry, offering users a convenient and efficient solution for organizing their vacations. With a solid foundation in place and a clear vision for the future, the Waga team is poised for continued success and innovation in the dynamic landscape of vacation planning app.

Contact Me

Feel free to reach out to discuss potential collaborations or if you have any questions. You can contact me via:

- Email: apogeeden@gmail.com

- Phone: +2348167431224

- LinkedIn: www.linkedin.com/in/destiny-owobu-a625bb111 

- Twitter: https://twitter.com/apogeeden

- GitHub:https://github.com/PBRAINS

- Website:www.bitacademy.mydurable.com

Thank you for visiting my portfolio!

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