Elhoseny ا.

SUMMARY

Data Analyst with experience in building automated ETL pipelines, predictive modeling, and data acquisition via

web scraping. Skilled in SQL, Power BI, and Python (Pandas, Scikit-learn) to generate actionablebusiness

insights through rigorous exploratory data analysis (EDA) and machine learning classification.

EDUCATION

Bachelor of Computer Science – Major in Artificial Intelligence 2021 – 2025

Arabic Open University, Egypt GPA: 3.0/4

EXPERIENCE

Commercial International Bank (CIB) Jul 2024 – Sep 2024

Internship - Transaction Data Analysis

• Analyzed 10,000+ rows of banking transaction data to support data-driven business decision-making.

• Cleaned and processed real transaction datasets to identify customer behavior trends and anomalies.

• Optimized prototype machine learning models using Python and Scikit-learn for predictive financial analysis.

Kayfa: Empowering Knowledge, Transforming Futures May 2026 – Jun 2026

Internship - Transaction Data Analysis& AI Agent

• Employee Attention Analytics Dashboard: Developed an interactive HR analytics dashboard using Streamlit to

analyze workforce behavior; delivered 7 key KPI-driven metrics that uncovered a critical 49% attrition spike among

high-risk cohorts to drive targeted retention strategies.

• Students Education Analytics Platform: Built a multi-source educational analytics platform using MongoDB to

normalize and process 8,000+ student records; integrated a statistical risk-scoring algorithm ($r=0.82$ correlation)

to proactively identify at-risk students and automate academic interventions.

• Kayfa AI Sales Agent (RAG + MCP): Developed an AI Sales Assistant using RAG, LlamaIndex, ChromaDB, and

MCP tools; systematized knowledge retrieval, customer interactions, and CRM-related workflows to optimize

business processes.

PROJECTS

Employee Attrition & Attention Analytics may 2026

• Engineered an End-to-End Analytics Pipeline in Python to integrate, clean, and process multi-source HR data from

CSV format, implementing strict business constraints for data quality and integrity.

• Enhanced an interactive HR analytics dashboard using Streamlit to analyze workforce behavior across multiple

demographics; delivered 7 key KPI-driven metrics that uncovered a critical 49% attrition spike among employees

with 3–6 years of tenure and long-distance commuters to drive targeted retention strategies.

• Designed behavior-driven visualizations using Plotly to isolate high-risk cohorts (entry-level, high-overtime, and low-

satisfaction segments), empowering HR teams to formulate targeted retention strategies. [ProjectLink]

Educational Performance & Student Engagement Dashboard may 2026

• Built a multi-source educational analytics platform using MongoDB to normalize and process 8,000+ student

records; integrated a statistical risk-scoring algorithm (r=0.82$ correlation) to proactively identify at-risk students and

automate academic interventions.

• Applied statistical analysis (Pearson correlation) to evaluate the direct impact of attendance, video watch time, and

platform engagement on final academic performance.

• Improved an automated Streamlit dashboard powered by a dynamic risk-scoring algorithm to trigger proactive academic

interventions.[Project Link]

E-commerce Data Analysis & Visalization May 2025

• Engineered an end-to-end data pipeline using SQL to process transactional data and derive business

KPIs, including Total Revenue ($503K).

• Cleaned and analyzed complex datasets using Python, generating data-driven visualization reports via

Matplotlib and Seaborn.

• Designed dynamic Power BI dashboards incorporating geospatial analysis, time-series forecasting, and

demographic segmentation to drive decision-making.[Project Link]

TECHNICAL SKILLS

Programming & DB: Python, SQL (SQL Server), MongoDB (No SQL)

Data Analysis: Pandas, NumPy, Exploratory Data Analysis (EDA), ETL Pipelines, Web Scraping

Visualization: Power BI, Excel, Tableau, Matplotlib, Seaborn

Machine Learning: Scikit-learn (Regression, Classification), Random Forest, Data Engineering, XGBoost

Deployment: FastAPI, REST APIs, Flask, Streamlit.

CERTIFICATIONS & LANGUAGES

• Certifications: Supervised ML (Coursera), Deep Learning with Keras (Coursera), NLP in TensorFlow

(Coursera), Decision Trees (DataCamp).

• Languages: Arabic (Native), English (Intermediate B2)