Moamen Abdelkawy is a Senior Economic Analyst at National Navigation Co. with over 15 years of experience bridging economics, data analysis, and machine learning. His expertise lies at the intersection of quantitative economics and maritime industry analytics, where he applies advanced econometric modeling and data science techniques to drive strategic decision-making.
With a strong foundation in both theoretical economics and practical data science applications, Moamen has established himself as an analytical polymath who transforms complex financial and economic data into actionable business intelligence. His intellectual curiosity and commitment to continuous learning have shaped a career characterized by innovation, technical excellence, and knowledge sharing.
Expertise in advanced econometric modeling, financial forecasting, and quantitative methods applied to real-world business challenges in the maritime sector.
Mastery of Python, SQL, and machine learning frameworks (TensorFlow, PyTorch), with particular strength in applying these tools to financial and economic datasets.
Distinguished teaching record with a 4.9/5 rating as Udacity mentor, demonstrating exceptional ability to communicate complex concepts and nurture talent.
As Senior Economic Analyst, Moamen conducts in-depth economic research within the maritime and shipping industry, utilizing advanced econometric modeling and quantitative methods. He leverages his proficiency in Python and key data analysis libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch) to perform economic forecasting and predictive modeling, informing strategic decision-making and growth initiatives. His responsibilities include developing analytical frameworks and financial models to optimize operational efficiency and creating insightful visualizations to communicate complex findings to stakeholders.
In his role at Udacity, Moamen reviews student projects in data science, Python programming, and programming fundamentals, providing detailed feedback that enhances students' technical skills and critical thinking. He leads virtual sessions for learners pursuing Nanodegrees in data analysis and data science, maintaining an exceptional average rating of 4.9/5.0. Additionally, he delivers interactive virtual sessions for students aged 12–17 as part of the Digital Egypt Cubs Initiative (DECI), focusing on foundational concepts in Data Science and Artificial Intelligence.
At Alexandria University, Moamen taught Microeconomics, Mathematical Economics, Econometrics, Macroeconomics, and International Economics to classes of up to 150 students. He provided academic guidance and contributed to examination administration and execution. A notable achievement during this tenure was co-establishing the Economic Society, which enhanced student engagement and understanding of economic concepts.
Oct 2023 - Oct 2025 (Expected)
Sep 2016 - May 2017
Oct 2008 - Jul 2010
Sep 2002 - May 2006
Graduated Summa Cum Laude, top of class
Deep learning-driven trading strategies using LSTM models for multi-asset portfolios, featuring prediction, backtesting, and tactical asset allocation.
GitHub RepositoryA comprehensive analysis and modeling project exploring Bitcoin price prediction using Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) architectures with advanced preprocessing.
GitHub RepositoryA minimal inventory management system built with Go, Gin, and GORM, featuring CRUD endpoints with UUIDs, rate limiting, and PostgreSQL integration complete with pagination, filtering, and sorting.
GitHub RepositoryComprehensive analysis and forecasting for a shipping line between Egyptian and Libyan ports, including trade volumes, profitability simulations, and advanced predictive modeling.
GitHub RepositoryAn in-depth exploration of Git functionality, demonstrating Moamen's ability to bridge technical concepts across economics, data science, and software development.
Read on Udacity BlogA comprehensive guide to implementing cross-validation methods in machine learning, highlighting Moamen's expertise in model validation and evaluation techniques.
Read on Udacity BlogA practical guide that demonstrates Moamen's understanding of the critical data preparation phase in machine learning projects.
Read on Udacity BlogUdacity
Nov 2024
DataCamp
Sep 2023
DataCamp
Sep 2023
Danish Ministry of Education
Sep 2016
Score: 170 | 99th Percentile
Jun 2023
Band 8.0 (L9.0, R8.5, W7.0, S7.0)
Nov 2019
Moamen Abdelkawy stands at the fascinating intersection of economics and cutting-edge data science, a rare combination that makes him exceptionally valuable in today's data-driven world. His ability to translate complex economic principles into actionable intelligence through the language of code and algorithms sets him apart as an analytical leader.
What truly distinguishes Moamen is his capability to bridge multiple worlds - seamlessly connecting theoretical economics with practical applications in the maritime industry, transforming complex financial data into predictive models that drive real business decisions, and building an impressive portfolio spanning Bitcoin price prediction to shipping line analysis.
His technical prowess is undeniable, but it's how he applies these tools that reveals his brilliance. As an educator, Moamen doesn't just share knowledge; he inspires excellence, as evidenced by his stellar ratings as a Udacity mentor. His technical writing demonstrates his gift for making complex concepts accessible to others, establishing him as the embodiment of modern analytical leadership - technically sophisticated, business-savvy, and committed to driving real-world impact through data.
