Mohamed Magdy

- Analyze and enhance central banking reports, focusing on Assets vs. Liabilities (ALM) to ensure accuracy and alignment with regulatory and financial standards. - Validate and reconcile data between core banking systems and the data warehouse to ensure consistency and completeness of reported figures. - Ensure proper classification of financial instruments, including loans, deposits, and investments, within reporting structures. - Perform detailed analysis on interest calculations, maturity buckets, and liquidity gaps to support financial insights and regulatory compliance. - Investigate discrepancies in reports, identify root causes, and resolve data and calculation issues to ensure data accuracy. - Improve reporting logic, data mappings, and calculation methodologies to enhance consistency, transparency, and audit readiness. - Optimize and tune complex SQL queries to improve performance, scalability, and reliability of reporting solutions. - Develop and maintain ETL processes using Informatica PowerCenter to integrate data from multiple sources into the data warehouse. - Build and enhance interactive dashboards and reports using Power BI to support business decision-making. - Collaborate with business stakeholders to gather requirements and translate them into effective data and reporting solutions. - Apply and validate business logic within reports to ensure alignment with business needs and regulatory requirements. - Perform data profiling, analysis, and validation to ensure high data quality and integrity. - Work with data from core banking systems and multiple sources to deliver comprehensive reporting and insights. - Continuously enhance reporting solutions by improving logic, resolving data issues, and increasing data transparency.

Worked as a data governance and data engineering specialist across leading organizations in Saudi Arabia, delivering enterprise-scale governance, classification, and data migration initiatives. Data Governance & Management Specialist – Arab National Bank Administered Informatica Axon as the enterprise data governance platform, enabling organization-wide adoption. Implemented data ownership and stewardship models, workflows, and governance KPIs. Governed Critical Data Elements (CDEs), aligned business and technical metadata, developed policies and glossaries, and supported governance councils through dashboards and reports to enhance compliance and maturity. Data Governance & Management Specialist – Saudi Post (SPL) Contributed to the Data Classification Exercise aligned with NDMO and NDI standards. Collaborated with the DMO to validate data elements, document classifications, conduct workshops, develop training materials, and support stakeholder engagement. Assisted in identifying and classifying CDEs and supported IDMC Data Governance and MCC for metadata scanning, lineage, and monitoring. Data Engineer – Alrajhi Takaful Supported large-scale data migration from Eska, Penta, and Siebel to Microsoft Dynamics 365 staging databases. Performed extraction, cleansing, deduplication, validation, and schema alignment while ensuring auditability, business rules enforcement, and scheduled ETL workflows. Data Governance Specialist – Neotek Configured Informatica EDC and Axon for metadata scanning, profiling, lineage, classification, and glossary management. Supported data quality initiatives and ensured alignment with Saudi NDMO standards, enabling transparency and traceability of critical data assets.

- Administer and operate Informatica Axon as the enterprise data governance platform, ensuring effective implementation and adoption across the organization. - Define, implement, and monitor data ownership and stewardship models, including roles, responsibilities, and approval workflows. - Identify, document, and govern Critical Data Elements (CDEs) to ensure consistency between business definitions and technical metadata. - Develop and maintain data governance policies, standards, and business glossaries in collaboration with business and technical stakeholders. - Work closely with data owners and business stewards to validate data definitions, classifications, lineage, and relationships. - Support data governance councils and working groups by preparing governance dashboards, KPIs, and Axon-based reports. - Contribute to improving data governance maturity by driving awareness, ensuring compliance with governance processes, and supporting continuous improvement initiatives.

- Work on the design, development, and optimization of complex data pipelines using Informatica PowerCenter, including advanced mappings, mapplets, and workflows, to integrate data across multiple platforms. - Implement data management strategies, including data quality monitoring, metadata management, and lifecycle governance. - Develop complex data models and transformations to accurately reflect business processes and support reporting needs. - Build and maintain ETL workflows and mapplets, optimizing performance, scalability, and reliability of BI infrastructure. - Create interactive and insightful dashboards to transform business requirements into actionable visualizations for decision-making. - Perform data profiling, root cause analysis, and validation to ensure data quality and integrity. - Write, test, and implement complex PL/SQL scripts, including triggers, procedures, and functions for business-critical workflows. - Collaborate with stakeholders to implement technical solutions aligned with business and regulatory requirements.

- Collaborate on the design and development of data pipelines, gaining practical experience in integrating data across multiple platforms. - Support the development of ETL processes, including PowerCenter mapplets, to extract and load data from multiple sources, such as databases, flat files, and XML files. - Collaborate on the design and development of data pipelines using Informatica PowerCenter, including simple mappings and workflows, gaining practical experience in integrating data across multiple platforms. - Assist in data profiling, cleansing, and transformation to ensure data quality and integrity. - Convert basic business requirements into simple, intuitive dashboards for reporting and analysis. - Assist in the maintenance and optimization of data models and queries for efficient data retrieval. - Support the implementation of PL/SQL scripts, including triggers, procedures, and functions, under guidance. - Collaborate with business stakeholders to gather requirements and translate them into technical solutions under supervision.

Projects: SAP Business Objects Migration to MicroStrategy Worked on migrating core banking reports from SAP Business Objects to MicroStrategy. Ensured accurate data mapping, report optimization, and seamless integration to enhance reporting efficiency. Dashboard Development for Budgeting and Retail Departments Designed and implemented interactive dashboards focusing on customer segmentation, assets portfolio, and facilities portfolio. Delivered actionable insights to support budgeting strategies and retail operations. SAP Business Objects Migration to Data Warehouse Worked on migrating SAP Business Objects reports into a centralized data warehouse. Conducted thorough data reconciliation during the migration process to ensure accuracy, consistency, and data integrity for enhanced reporting and analysis capabilities. - Migrated SAP Business Objects reports and dashboards to a new Data Warehouse, FlexCube Core Banking System, and Temenos T24 system. - Analyzed and migrated budgeting and retail MIS reports from FlexCube core banking to a historical DWH, creating general datasets via MicroStrategy BI for future reporting and dashboards. - Gathered requirements from business stakeholders and translated them into technical solutions. - Maintained and enhanced BI infrastructure, including data pipelines, models, and reporting solutions. - Developed impactful dashboards by translating business needs into effective data visualizations. - Utilized MicroStrategy BI to develop, maintain, and optimize reports and dashboards, ensuring data accuracy and accessibility for users. - Created and managed general datasets in MicroStrategy for efficient reporting and business needs. - Enhanced reporting processes with advanced MicroStrategy features, improving decision-making and insights. - Optimized data models and queries for efficient and accurate data retrieval. - Performed data profiling, cleansing, and transformation to ensure data quality and integrity.

- Delivering comprehensive training sessions on Excel and Power BI, covering introductory to advanced topics, ensuring a smooth learning experience and timely technical support. - Guiding trainees through a technical Journey of Discovery in Excel and Power BI, showcasing their capabilities and benefits for improved Data analysis, Visualization, and Dashboarding. - Instructing trainees on creating robust data models, compelling visualizations, and sharing reports in both Excel and Power BI, fostering effective communication and collaboration within teams. - Providing clear explanations and demonstrations of concepts such as database conceptual modeling, database logical and physical modeling, SQL programming, data query language, data manipulation language, and data definition language. - Teaching trainees problem-solving techniques using SQL and Python.

- Delivering comprehensive training sessions on various topics related to data science, including descriptive statistics, linear algebra, database management systems, SQL, data analysis, data transformation, data visualization, Python programming, machine learning, and deep learning. - Guiding trainees through hands-on exercises, allowing them to gain practical experience and reinforce their understanding of data science concepts. - Providing clear explanations and demonstrations of concepts such as database conceptual modeling, database logical and physical modeling, SQL programming, data query language, data manipulation language, and data definition language. - Teaching trainees problem-solving techniques using SQL and Python. - Instructing trainees on data analysis techniques, including data cleaning, transformation, and exploration using tools such as pandas and NumPy. - Introducing trainees to data visualization and dashboarding using tools like Power BI and Tableau. - Teaching Python programming language, including data structures, object-oriented programming, and its application in data science. - Educating trainees on supervised machine learning algorithms such as linear regression, support vector machines, logistic regression, decision trees, and ensemble methods. - Instructing trainees on unsupervised machine learning techniques such as clustering and dimensionality reduction. - Demonstrating the application of machine learning models using popular libraries like scikit-learn. - Guiding trainees on model deployment techniques, including REST APIs and Streamlit. - Introducing trainees to deep learning concepts and techniques, including single and multiple layer perceptron models. - Staying up-to-date with the latest trends and advancements in data science, including tools, techniques, and algorithms, and continuously enhancing your own knowledge and skills.

- Delivering training sessions on Power BI, covering a range of topics from introductory to advanced levels. - Answering trainee questions and providing timely technical support to ensure a smooth learning experience. - Guiding trainees on a technical Journey of Discovery, helping them explore and understand the capabilities of Power BI. - Creating and maintaining training materials, including presentation slides, hands-on exercises, and reference guides. - Demonstrating the benefits of using Power BI, such as improved data analysis, visualization, and reporting capabilities. - Teaching trainees how to create effective data models in Power BI, including establishing relationships between tables and creating calculated columns and measures. - Instructing trainees on how to create compelling visualizations using various chart types, applying formatting techniques, and utilizing filters to enhance data insights. - Educating trainees on how to publish and share reports using Power BI, ensuring effective communication and collaboration within teams. - Exploring advanced topics in Power BI, such as utilizing DAX to create custom calculations and integrating Power BI with other Microsoft products. - Staying up-to-date with the latest developments in Power BI and continuously enhancing your own knowledge and skills.

• Design, Code, and Test Machine learning Models to Predict and develop work in the organization. • Collecting validating and analyzing customer data. • Design and code the Human Resources Payroll Reporting System that helps them generate Payroll reports. • Identify, analyze, and interpret trends or patterns in complex data sets. • Work with management to prioritize business and information needs. • Monitor trends and identify improvement areas. • Producing reports and charts communicating trends within data to non-specialists. • Integrate Multiple data sources into one visualization to tell a story. • Develop analytical reports and Represent large Complex sets of data through visuals. • Create robust, reusable data querying, transformation, and visualization processes in PowerBI, SQL, Python, and Excel. • Filter and Clean data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems. • Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality. • Creating the data pipeline for training the model, Validating the ML model, and finally persisting the ML model to production.

- Design an automated Human Resources Payroll Reporting System. The System analyzes employee data for more than 4 companies cleans the data and applies a lot of payroll transformation to it then the system generates more than 4 different complex reports. those reports take 6 days to finish and require 3 employees to work on them, but the system finishes them in less than 5 minutes. - Leverages the power of Excel, Visual Basic, and data visualization to streamline HR employee metrics management. In collaboration with managers, I developed a user-friendly Excel form and a comprehensive dashboard comprising two pages. The first page of the dashboard provides managers with valuable insights into their team's overall performance. It showcases key metrics and trends, enabling managers to make data-driven decisions and identify areas for improvement. This page offers a high-level view of the organization's workforce, empowering managers to optimize their team's performance and drive productivity. The second page of the dashboard focuses on individual employee performance. It allows managers to view detailed metrics and ratings for each employee, providing a comprehensive overview of their strengths and areas that require development. This data-driven approach aims to foster employee growth and enable targeted coaching and support. By automating the data collection process using Excel's Visual Basic, managers can efficiently enter and update employee ratings through a user-friendly form. This eliminates manual data entry and reduces the risk of errors, ensuring accuracy and consistency in the HR metrics.

- Interpreting data, and analyzing results using statistical techniques. - Developing and implementing data analyses, data collection systems, and other strategies that optimize statistical efficiency and quality. - Acquiring data from primary or secondary data sources and maintaining databases. - Identify, analyze, and interpret trends or patterns in complex data sets

Data Analytics Virtual Experience consists of 4 steps: 1:Project Understanding Quickly get up to speed with the business problem being addressed, project requirements, and team alignment. 2:Data Cleaning & Modeling Modeling data to create valuable insights. 3:Data Visualization & Storytelling Bring our data to life and uncover insights for the business. 4:Present to the Client It’s my time to shine by presenting my insights back to the client.

- Master’s degree in Scientific Computing and Data Science. - I delve into cutting-edge subjects such as Signal Processing, Computer Vision, Operation Research, Computational Neural Networks, Cloud computing, and Time series analysis, equipping myself with a comprehensive understanding of advanced concepts in the field of computer science.

Graduation Project Grade : A+ During my studies, I had the opportunity to delve into the fascinating world of computer science and explore various topics such as programming, algorithms, data structures, and artificial intelligence. I'm especially proud of the work my team and I did on our graduation project, where we developed a breast cancer classification model using a graph neural network on Eastern mammogram images. Thanks to our efforts, we were able to achieve an accuracy of 95.8% in classifying mammograms as normal, benign, or malignant.

I completed a comprehensive Full Stack Python Web Application Development track from the Information Technology Institute. Over the course of 60 hours, I gained a solid foundation in various aspects of web development, including Python programming, data structures, object-oriented programming, algorithms, databases, HTML, CSS, JavaScript, Bootstrap, Flask, and both frontend and backend development. Throughout the track, I gained practical hands-on experience by working on real-world projects, allowing me to apply my knowledge and develop functional web applications. I learned how to design and implement efficient algorithms, create responsive and visually appealing user interfaces with HTML, CSS, and Bootstrap, and utilize JavaScript to enhance user interactivity. Furthermore, I gained proficiency in Python, mastering its object-oriented programming. I honed my skills in working with databases, specifically integrating them into web applications using frameworks like Flask.

The data science course I took comprised 8 units that covered critical aspects of the field, including data cleaning, exploratory analysis, statistical modeling, machine learning, and data visualization. The program provided a comprehensive curriculum that allowed me to acquire a solid understanding of fundamental concepts and techniques used in data science. Throughout the course, I gained an in-depth knowledge of various components of data science, and I developed a holistic view of the field. I honed my skills in data manipulation, statistical modeling, and machine learning algorithms. I also learned how to effectively communicate complex data insights through data visualization techniques. Overall, the course broadened my knowledge and understanding of data science, giving me the confidence to apply my newly acquired skills to real-world problems.