Open to Data Science for Marketing & Analytics opportunities

Marketing × Data × Machine Learning

I turn customer and product data into smarter business decisions.

I'm Ziad Ibrahim, a marketing graduate building at the intersection of customer analytics, machine learning, and business strategy. I use data to understand customer behavior, uncover patterns, and translate analysis into practical marketing recommendations.

Explore my work View resume

About me

A marketer who learned to work with the data behind the decisions.

My academic background is in marketing, but I became increasingly interested in the data behind customer behavior: why people buy, why they leave, how campaigns perform, and how businesses can make better decisions from those signals.

That curiosity led me to Python, SQL, statistics, machine learning, Excel, Tableau, and Google Analytics 4. My projects connect customer segmentation and campaign performance analysis with practical marketing questions and recommendations.

I also have hands-on AI training experience evaluating text, audio, and visual model outputs, which strengthened my attention to detail, consistency, and analytical judgment.

Selected work

Projects built around business questions, not just models.

Each project follows the same principle: define the business problem, understand the data, choose the right analytical method, and communicate what the business can do next.

Customer Segmentation

Customer segmentation dashboard and business insights

01 Customer Analytics · Machine Learning

Customer Segmentation Analysis

Built a customer-level analytical dataset from e-commerce transactions and used K-Means clustering to identify meaningful customer groups based on spending, order frequency, average order value, and recency.

Business question

How can the company treat different customer groups with more relevant marketing strategies?

What I did

SQL aggregation, feature engineering, scaling, K-Means, Elbow Method, interpretation, and dashboards.

Marketing output

Recommendations for VIPs, frequent buyers, lower-value customers, and inactive customers.

Python SQL Pandas NumPy Scikit-learn Excel Tableau

View GitHub repository ↗ Full case study coming next

Marketing Campaign Analysis

Marketing campaign analysis screenshot 3

Select an image to view it at full size.

02 Marketing Analytics · Regression

Marketing Campaign Analysis for Optimization

Completed a YouTube-guided analysis of how email, flyer, and phone campaigns, together with sales contacts, relate to the amount collected from clients. Practiced regression analysis and ROI interpretation to explore opportunities for campaign improvement.

Business question

Which marketing channels and sales contacts are associated with better client outcomes?

What I practiced

Pandas analysis, OLS regression, coefficient and p-value interpretation, client-type comparisons, and ROI calculations.

Learning outcome

Explored how regression findings and cost assumptions can inform campaign targeting and priorities for further testing.

Python Pandas Statsmodels OLS Regression ROI Analysis Jupyter Notebook

View GitHub repository ↗ YouTube-guided learning project

Coming soon

Product Analytics

Product Analysis Dashboard

Excel-based analysis focused on product performance, KPIs, customer behavior, and decision-ready reporting.

ExcelAnalyticsDashboard

In progress

Predictive Marketing

Customer Purchase Propensity

Predicting purchase likelihood from customer behavior using statistics, feature engineering, SQL, and machine learning.

PythonSQLMLStatistics

Experience

Practical experience across data projects and AI training.

I have developed hands-on experience by building end-to-end data science and marketing analytics projects, alongside professional AI training and evaluation work.

Portfolio Projects Ongoing

Data Science & Marketing Analytics Projects

Applied analytics, machine learning, dashboards, and business recommendations

Built an end-to-end customer segmentation project using Python, SQL, K-Means, Excel, and Tableau.
Completed a YouTube-guided campaign analysis using Pandas and Statsmodels to practice OLS regression and ROI interpretation.
Engineered customer-level features from transactional data, including spending, frequency, average order value, and recency.
Translated analytical results into practical marketing recommendations for retention, loyalty, reactivation, and personalization.

Outlier 3 months

AI Trainer

Text, prompt, and audio evaluation

Evaluated AI-generated responses for quality, relevance, and instruction following.
Reviewed prompts and model outputs using structured evaluation criteria.
Worked on audio-focused tasks including recording and evaluating spoken content.

Remo Expert 6 months

Generalist AI Trainer — Visual Content

Visual generative AI evaluation

Evaluated AI-generated visual content against quality and task-specific criteria.
Reviewed images for visual inconsistencies, prompt alignment, and instruction-following issues.
Provided consistent human feedback to support model improvement.

Toolkit

The tools I use to move from raw data to a marketing recommendation.

Programming & Data

Python · NumPy · Pandas · SQL · Jupyter · Data Cleaning · Feature Engineering

Machine Learning

Scikit-learn · Statsmodels · Regression · Classification · Clustering · Model Evaluation · K-Means

Marketing Analytics

Customer Analytics · Segmentation · Campaign Analysis · ROI Interpretation · Marketing Metrics · Google Analytics 4

Visualization & BI

Excel · Tableau · Matplotlib · Dashboard Design · Data Storytelling

Math & Statistics

Probability · Statistics · Linear Algebra · Calculus · Mathematical Foundations for ML

Additional

Algorithms · Data Structures · Git · GitHub · Prompt Engineering · HTML · JavaScript

Education & learning

A business foundation with a technical learning path.

University

Bachelor's Degree — Faculty of Business

Alexandria University

Marketing specialization with a foundation in consumer behavior, market research, business strategy, and marketing principles.

Professional learning

Data, ML & Marketing Analytics

Machine Learning Specialization
Meta Marketing Analytics
IBM AI Developer
Mathematics for Machine Learning
Probability & Statistics
Google Analytics 4

Let's connect

Looking for someone who understands both customers and data?

I'm interested in opportunities across Data Science for Marketing, Marketing Analytics, Customer Analytics, AI training, and applied machine learning.

Email me LinkedIn ↗ GitHub ↗