Customer Churn Analysis
Cleaned and prepared a telecom customer dataset using Python and SQL, then analyzed churn patterns across different customer segments.
Hello, I'm
Statistics and Computer Science student building a career across Data Analysis and Data Engineering.
I'm Haneen Omar, a Statistics and Computer Science student at Mansoura University, building my career across Data Analysis and Data Engineering.
My background combines statistical thinking, programming, and data technologies, with hands-on experience in Python, SQL, Excel, Power BI, relational databases, ERD design, ETL, and data pipelines.
I enjoy working with data to uncover patterns, solve analytical problems, and transform raw information into clear, useful insights that support better decisions.
What sets me apart is the combination of Statistics and Computer Science — allowing me to approach data from both an analytical and technical perspective.
I'm interested in opportunities where I can contribute to data-driven teams, build practical solutions, and continue growing as a data professional.
Let's connect and turn data into something meaningful.
Finding patterns & insights
ETL & data pipelines
Python & SQL
Analytical thinking
Bachelor of Science in Statistics and Computer Science
Completed approximately 120 hours of practical training in Data Analysis.
Worked with SQL, Excel, Power BI, Python, Statistics, ERD and relational databases.
Practiced data analysis workflows including working with databases, analyzing datasets, and creating visual reports and dashboards.
Currently participating in a 6-month Data Engineering training program.
Studying ETL, data pipelines, Object-Oriented Programming, algorithms and data structures.
Building technical foundations for working with data engineering workflows and developing practical data solutions.
Programming and computer science fundamentals for data-focused applications.
Analyzing datasets and transforming raw data into useful insights.
Building dashboards and visual reports to communicate data clearly.
Working with structured data, ETL processes and data pipeline concepts.
Practical projects combining data analysis, SQL, visualization and business-oriented insights.
Cleaned and prepared a telecom customer dataset using Python and SQL, then analyzed churn patterns across different customer segments.
Applied advanced SQL using joins, grouping and aggregations across a multi-table relational database.
Organized logistics for public events, administrative meetings and cultural venue activities while contributing to team coordination, event management and communication.
Interested in data analysis, data engineering and building practical data-driven solutions? Let's connect.