I am an Industrial Mathematics graduate specializing in Data Analytics and Process Automation. My work focuses on building efficient data pipelines and extracting technical insights from complex datasets to drive strategic growth.
- Data Analysis: Microsoft Excel (Advanced Functions & VBA), Python (Pandas, NumPy), SQL (PostgreSQL/MySQL)
- Visualization: Plotly Dash, Matplotlib, Seaborn, Folium, Microsoft Excel (Dashboards)
- Technical Workflow: ETL Pipelines, Web Scraping, Relational Database Design, Time-Series Analysis, Exploratory Data Analysis (EDA)
Tools: Python (Dash, Plotly, Pandas, Seaborn, Folium)
- Developed an interactive web dashboard to analyze 40 years of automobile sales data, uncovering how recessions structurally reshape market demand.
- Technical Achievement: Engineered a reactive callback system in Dash to toggle between "Recession Period" and "Yearly" statistics, featuring 8 distinct analytical charts.
- Strategic Insights: - Identified a 4–5% unemployment threshold that triggers a total demand collapse in premium segments (Sports/Executive).
- Quantified the "Flight to Utility," where SuperMiniCars maintained volume while luxury segments dropped by ~75% during downturns.
Tools: SQL (SQLite), Python (Pandas), ipython-sql
- Engineered a relational database to investigate the intersections of crime, education, and socioeconomic conditions in Chicago.
- Technical Achievement: Developed a clean ETL pipeline to migrate unstructured civic CSV data into optimized SQL tables, solving 10 complex relational problems with 100% accuracy.
- Strategic Insights:
- Quantified the strong correlation between hardship indices and crime concentration, identifying Austin as the most crime-prone area.
- Benchmarked school safety across the city, revealing that middle schools faced the highest safety challenges.
Tools: Python (yfinance, BeautifulSoup, Matplotlib, Pandas)
- Automated a live data-harvesting pipeline to analyze the correlation between stock market valuation and quarterly revenue.
- Technical Achievement: Engineered a custom web scraper to extract quarterly revenue from unstructured HTML tables, bypassing standard API limitations.
- Strategic Insights:
- GameStop (GME): Quantified the historic decoupling of stock price from fundamental revenue during early 2021, illustrating sentiment-driven market volatility.
Tools: Microsoft Excel, Google Forms, Automated Google Sheets Pipeline
- Developed a full-cycle data solution to transition a manual monitoring system into an automated digital ecosystem for Word Point Ministries.
- Impact: Identified the University of Ilesa as the engagement lead and isolated low-performing centers for strategic leadership follow-up.
Tools: Maple, LaTeX
- Developed a high-order (Order 6) numerical algorithm to solve general second-order Ordinary Differential Equations (ODEs) directly.
- Academic Achievement: Validated accuracy against established research and achieved a high-precision error constant, forming the foundation of my analytical precision.
| Automobile Dashboard | Stock Analysis | WPM DWR Dashboard | Numerical Modeling |
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| Interactive Economic Trends | Python ETL & Data Harvesting | Automated Ministry Ecosystem | Order 6 Numerical Convergence |
I am a 3MTT Fellow and ForbesBLK Member dedicated to technical excellence in Data Analytics. I focus on "learning in public" by documenting technical workflows, data integrity processes, and automation logic.
I believe that a Data Analyst's greatest tool is the ability to present findings without bias. While I am constantly learning and refining my skills, I am committed to documenting the "why" behind the "what". You can find my recent lessons documented here and on my LinkedIn.
- LinkedIn: linkedin.com/in/emycodes
- Role Interests: Data Analyst, Business Intelligence Analyst, Product Analyst, Operations Research.
"Data is most powerful when it serves as a clear, honest bridge between raw numbers and strategic growth."
©️ EmyCodes | 2026