Ramadan Ahmed

Data Scientist
Lagos, NG.

About

Highly analytical Data Scientist with expertise in SQL, MongoDB, AI evaluation, and machine learning model development, leveraging Python for data wrangling, exploratory data analysis, hypothesis testing, and model deployment. Proven ability to transform complex datasets into actionable insights, driving informed business decisions and optimizing operational efficiency. Passionate about applying advanced analytical techniques to solve real-world problems and contribute to data-driven innovation.

Work

WQU
|

Deep Learning Intern

Summary

Developed and deployed predictive models using linear regression and multi-layer neural networks to enhance material selection processes in construction.

Highlights

Developed linear regression models and multi-layer neural network models to accurately predict the compressive strength of concrete, contributing to informed decision-making on choice materials for building construction.

WQU
|

Data Science Lab Intern

Summary

Led data analysis and model development projects, applying advanced statistical and machine learning techniques to derive actionable insights for various business and scientific challenges.

Highlights

Conducted exploratory data analysis (EDA) on 21,000 Mexican properties using pandas, matplotlib, boxplots, and seaborn, assessing price influences to provide data-driven purchase insights.

Developed ARIMA and ARMA models with hyperparameter tuning in Python (pandas, plotly express, matplotlib, seaborn, statsmodels) to forecast PM2.5 concentrations in Nairobi and Dar es Salaam, supporting proactive pollution control.

Built Logistic Regression and Decision Tree models with scikit-learn from SQLite data to predict building damage from the 2015 Nepal earthquake, identifying low-strength materials as a major risk factor.

Deployed Decision Tree and Gradient Boosting models using Python (pandas, matplotlib, plotly express, seaborn, scikit-learn) to predict company bankruptcy in Poland and Taiwan, aiding strategic investment decisions.

Performed end-to-end customer segmentation using k-means clustering on 20k+ U.S. household records (351 variables), resulting in 4 actionable segments and an interactive Dash dashboard for non-technical stakeholders.

Designed and executed a randomized A/B experiment using MongoDB applicant data, performing chi-square analysis and building ETL pipelines and an interactive web app to inform evidence-based decision-making.

Built and deployed an end-to-end volatility forecasting pipeline for MTN Group equity data, integrating API-based data ingestion (Alpha Vantage), SQLite storage, and GARCH(1,1) modeling, improving reproducibility and enabling programmatic forecasts.

Ramy's Crave and Glup
|

Data Analyst

Lagos, Lagos, Nigeria

Summary

Managed real-time data collection and analysis, leveraging data visualization tools to optimize inventory and boost profitability by over 35%.

Highlights

Supervised real-time stock and sales data collection, storing records in Microsoft SQL Server and reducing data loss by 60%.

Analyzed stock and material usage trends in Excel, enabling timely restocking and reducing average customer wait time by 4 minutes.

Designed Power BI and Tableau dashboards to visualize product sales, optimizing inventory decisions and boosting profit by 35%+.

Turing
|

Business Analyst

Palo Alto, California, US

Summary

Streamlined data processing and visualization, designed dynamic dashboards, and captured workflow data to support targeted advertising and AI model fine-tuning, reducing costs by 10%.

Highlights

Cleaned and preprocessed datasets, created pivot tables, and designed dynamic Excel dashboards to visualize sales-demographic relationships, enabling targeted advertising and reducing costs by 10%.

Captured screen recording of workflow and converted task sequences into structured JSON files to support the fine-tuning of Anthropic AI models.

University of Abuja
|

Research Intern

Abuja, Abuja, Nigeria

Summary

Optimized experimental design and data analysis processes, developing predictive mathematical models and creating graphical illustrations for effective research interpretation and a 40% cost reduction.

Highlights

Designed experiments, achieving a 40% cost reduction through literature review, safety analysis, and optimization using MATLAB and Excel.

Conducted data analysis using Excel, removing over 80% of data anomalies for improved accuracy and reliability.

Developed predictive mathematical models with Python (pandas, scikit-learn) and MATLAB to aid forecasting of experimental results and the design of commercial Direct Air Capture devices.

Created graphical illustrations in Excel and MATLAB for effective analysis and interpretation of research results.

Muhasu Enterprises
|

Intern

Lagos, Lagos, Nigeria

Summary

Monitored and analyzed production data to optimize machine scheduling and reduce operational costs by 20%.

Highlights

Monitored and analyzed production data by managing extensive logs of polythene roll weights, identifying a clear relationship between weight and machine run time.

Developed a predictive mathematical model using Lagrange interpolation, optimizing machine scheduling and reducing labor costs by 20%.

Volunteer

University of Abuja
|

Volunteer Research Member

Abuja, Abuja, Nigeria

Summary

Contributed to research by conducting data collection, analysis, and model development, significantly improving computational efficiency.

Highlights

Conducted data collection, analysis, and visualization in Excel, significantly reducing Python computation time.

Processed and normalized datasets in Python (pandas, numpy) for machine learning model development.

Trained an Artificial Neural Network (ANN) for predictive control using MATLAB, contributing to a novel machine learning model.

Education

WorldQuant University

Professional Program

Applied Data Science and Deep Learning

Courses

Exploratory data analysis

Data Visualizations

Machine learning model building and deployments

Ethics in machine learning

University of Abuja
Abuja, Abuja, Nigeria

B.Eng

Chemical Engineering

Grade: 4.77/5.0 (First Class Honours)

Courses

Probability and statistics

Python and C programming

Calculus

Algebra

Technical Writing and Presentation

Languages

English
Yoruba

Awards

Overall best male graduating student, University of Abuja

Awarded By

University of Abuja

Recognized as the best graduating male student in the entire University of Abuja for the 2023/2024 academic session.

Touch-A-Life Foundation Scholarship Award

Awarded By

Touch-A-Life Foundation

Named a TAL scholar for outstanding academic performance in STEM and received full funding to study chemical engineering in the University of Abuja for 5 years.

Asherkine-TS Academy Scholarship

Awarded By

TS-Academy

Received tuition fee scholarship to study Data Science in TS-Academy.

ALX-Mastercard Foundation scholarship

Awarded By

Mastercard Foundation

Awarded a Mastercard Foundation scholarship tuition fee award to study software engineering at ALX Africa.

Chinese Embassy Scholarship and award of academic excellence

Awarded By

The Chinese Embassy in Nigeria

Received an award of honor for academic excellence and a tuition fee award of One Hundred Thousand Naira for the 2020/2021 academic session.

Skills

Data Analysis & Visualization

Exploratory Data Analysis (EDA), Data Visualizations, Hypothesis Testing, Cluster Analysis, Customer Segmentation, Root-Cause Analysis, Data Wrangling, Statistical Analysis, A/B Testing, Chi-square Analysis, Data Anomalies, Graphical Illustrations, Dashboards, Heatmaps, Interactive Plots, Power BI, Matplotlib, Pandas, Plotly Express, Seaborn, Tableau, Excel, MATLAB.

Machine Learning & AI Development

AI Evaluation, Machine Learning Model Development, Model Deployment, Deep Learning, Linear Regression, Multi-layer Neural Networks, ARIMA, ARMA, Scikit-Learn, Tensorflow, Logistic Regression, Decision Tree, Gradient Boosting, K-means Clustering, Artificial Neural Network (ANN), Volatility Forecasting, GARCH(1,1) Modeling, Model Optimization, Hyperparameter Tuning, Model Selection, Anthropic AI Models.

Programming & Databases

Python, C Programming, Javascript, SQL, MongoDB, SQLite, JSON, API Integration (Alpha Vantage), Web Scraping (Requests, BeautifulSoup), Numpy, Statsmodels, FastAPI.

Project Management & Communication

Report Writing, Stakeholder Engagement, Problem-Solving, Strategic Planning, Presentation, ETL Pipelines, Interactive Web App Development, Experiment Design, Workflow Optimization, Executive Summaries, Microsoft Powerpoint, Microsoft Word.

Projects

Statistical Failure analysis of an AI Agent

Summary

Performed multi-dimensional failure analysis on AI model outputs to identify systemic error patterns, conduct root-cause analysis, and recommend improvements for enhanced accuracy.

Webscraping of Jumia Website for Skincare Product Data

Summary

Built a full web-scraping pipeline to extract structured product data, engineered a similarity algorithm, and delivered actionable insights through visualizations for product analytics.

Customer Churn Prediction Using Random Forest Model

Summary

Completed a customer churn analysis simulation for XYZ Analytics, involving data identification, advanced data exploration, and Random Forest model optimization.