Help & Supportcareers@gravityer.com
Data Science with 2+ years in Analytics & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Scientist passionate about analytics, optimization, and decision science, with a strong background in statistical modeling and machine learning. Focused on applying operations research and data transformation and data-driven methods to solve complex business issue and support smarter, evidence-based business opportunity decisions.
Information Technology Institute
Professional Training Program · Data Science Track
October 1, 2025 – June 1, 2026
Cairo University
Bachelor in Operations Research and Decision Support · Computers and Artificial Intelligence
September 1, 2020 – July 1, 2024
Misr International University
Computer Science Teaching Assistant
February 1, 2025 – October 1, 2025
India
iSchool
Part-Time Coding Instructor
August 1, 2024 – December 1, 2024
India
Telecom Egypt
Cyber security Internship
July 1, 2022 – August 1, 2022
India
Race to the Pit – Strategic Pit Stop Optimization in Formula 1
June 1, 2026 – Present
Modeled pit strategies using Nash equilibrium and backward induction. Evaluated optimal timing and tire choices considering degradation, undercutting, and overtaking.
Oil Waste Collection Using Hybrid Particle Swarm and Simulated Annealing Algorithm
June 1, 2026 – Present
Solved MTSP for oil waste collection using a hybrid Particle Swarm + Simulated Annealing algorithm. Optimized routing to reduce cost and environmental impact; improved efficiency in simulations.
View ProjectBash Shell Script DBMS
June 1, 2026 – Present
Built a Bash-based command-line DBMS using a file-system-based architecture. Implemented CRUD operations with data type and primary key validation. Added a SQL-like command interface for database operations.
View ProjectCustomer Engagement Analysis in Excel
June 1, 2026 – Present
Analyzed 2022 student engagement using regression, ANOVA, and correlation in Excel. Identified trends showing the effect of new platform features.
Home Credit Default Risk Prediction
June 1, 2026 – Present
Developed an end-to-end machine learning pipeline to predict loan default risk using customer financial and credit data. Performed data cleaning, feature engineering, and model training using LightGBM and Random Forest. Improved model performance through hyperparameter tuning and interpreted predictions using SHAP.
View ProjectNLP Intelligence System: From Raw Text to Production
June 1, 2026 – Present
Built an NLP pipeline for text preprocessing, tokenization, stemming, lemmatization, and vectorization. Compared BoW, TF-IDF, BM25, and word embeddings on real-world noisy text datasets. Developed a sentiment classifier and BM25-based search engine with sentiment filtering. Tracked experiments using MLflow and versioned data using DVC. Deployed the best model as a Dockerized FastAPI service.
View ProjectDecision Making and Reinforcement Learning
Columbia University
June 1, 2026 – Present
Generative AI with AWS
Udacity
June 1, 2026 – Present
Database Fundamentals
ITI
June 1, 2026 – Present
Data Science with Python
HarvardX
June 1, 2026 – Present
Python Programmer Bootcamp
365 Data Science
June 1, 2026 – Present
IBM Dada Analyst Specialization
IBM
June 1, 2026 – Present
Fit in deutsch A2
GOETHE
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from NLP and predictive modeling to optimization and even a Bash DBMS, indicates a broad intellectual curiosity and adaptability. Their academic background in Operations Research and Decision Support, combined with practical ML projects, aligns well with a data science role that requires both theoretical depth and practical application. The teaching experience also suggests a willingness to share knowledge and contribute to a learning environment. The candidate's experience level (2) is junior to mid-level, which might require some mentorship for a senior role, but their foundational skills are strong.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their project work, particularly in applying complex algorithms to real-world scenarios. Their teaching assistant and coding instructor roles suggest good communication and mentoring abilities. The project descriptions indicate a structured approach to problem-solving and an understanding of end-to-end ML pipelines. However, the resume does not provide explicit details on teamwork or leadership within projects, which are crucial for senior roles.