Hello, I'm
Ahmed Ramadan
Data Scientist & Data Analyst
Turning data into insights that matter.
Turning data into insights that matter.
My journey of continuous learning through online platforms and YouTube resources
As a Data Analyst and Data Scientist, I start by deeply understanding the business I’m working with. I then analyze its data — whether simple or complex — and develop dashboards that highlight the root of the problem and help define strategies for immediate improvement. I also build machine learning models to predict what may happen in the near or distant future, and based on these predictions, I help craft robust strategies to enhance the business’s productivity and growth.
The dashboard analyzes Uber trip patterns to identify busiest periods, peak demand seasons, and key performance metrics such as pickup rate, trip duration, and fare. Insights are visualized in Power BI for data-driven decision making.
Design and develop a comprehensive dashboard to monitor and analyze key business metrics across sales, revenue, customer behavior, and shipping operations.
Developed an interactive dashboard to track and analyze employee turnover trends. Helped HR teams identify key attrition drivers and improve retention strategies through segmentation of attrition rates, demographic insights, compensation gap analysis, and categorized exit interview feedback.
Analyzed flight data to identify the important features influencing ticket prices.
Analyzed Zomato data to uncover key factors for restaurant success and built an XGBoost model with hyperparameter tuning to predict success probability.
Dream Housing Finance company deals in all home loans. They have presence across all urban, semi urban and rural areas. Customer first apply for home loan after that company validates the customer eligibility for loan. Company wants to automate the the loan eligibility process (real time) based on customer detail provided while filling online application form.
The aim of the project :
Build Machine learning model to help company to automate the loan eligibility process (real time) based on customer detail provided while filling online application form.
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
The aim of the project :
Build machine learning model to detection anomaly (fraud).
we need to create a customer segmentation model to recommend the best merchants for each user as targetted offers About Data : Data is a transnational dataset which contains all the transactions with his merchant name , the number of times the customer purchased from the merchant, the points the customer owns, etc.
This data was collected in 2019 and its about detials of air flight tickets in india and in this project will predict price of tickets. The Air flights has specifc from city (Source) to city (Destnation) Like : Delhi To Cochin Kolkata To Banglore Banglore To Delhi and New Delhi Mumbai To Hyderabad Chennai To Kolkata
What is objective of this project ?
After analyze data and know what is the important features that influence in air flight ticket price , Now i can predict this ticket price.
The dataset contains simulated customer behavior on the Starbucks Rewards mobile app. It includes demographic data about users, transactional data showing purchases with timestamps and amounts, and offer data recording when users receive, view, and complete offers. Offers can be either informational (ads) or actual promotions like discounts or BOGO (buy one get one free). Each offer has a validity period during which it can influence customer behavior. Not all users receive the same offers, and some weeks users may not receive any offer at all.
What is objective of this project ?
The goal of this project is to analyze and combine transaction, demographic, and offer data to determine which demographic groups respond best to which type of offer. This helps to understand how different offers influence customer purchasing behavior across different segments, enabling more targeted and effective marketing.
I'll get back to you as soon as possible
Let's connect! I'm open to opportunities
Looking forward to collaborating on data-driven projects or discussing how I can help your organization leverage data for better decision making.