Jana Alnajem

Supported end-to-end SAP Business One implementations from requirements to configuration, testing, and go-live support. Analyzed client business processes and mapped them to SAP B1 best-practice solutions. Configured and maintained core master data including Business Partners, Item Master Data (batch/serial), Chart of Accounts, and warehouses/bin locations. Implemented and tested key business cycles (sales, purchasing, inventory, and production) and assisted with production BOM, production orders, and goods issues/receipts. Performed data migration and validation using Data Transfer Workbench (DTW) and Excel templates, including opening balances. Developed and executed SQL queries through SAP B1 Query Generator for reporting and reconciliation. Supported creation and maintenance of user-defined fields and reports, assisted with GL account determination rules, and resolved system/posting errors during testing and live databases. Participated in UAT and helped with user training, while p

Provided customer service and maintained a positive guest experience in a fast-paced coffee shop environment. Covered front-of-house roles including hostess (guest reception and seating coordination), runner (order coordination and service support), and waitress (order taking, delivery, and customer follow-up). Handled customer inquiries, complaints, and feedback professionally to ensure satisfaction. Coordinated daily operations between front-of-house and kitchen teams. Managed cash transactions and payment processing in compliance with internal procedures, and supported opening/closing activities including cash reconciliation and basic accounting records. Maintained cleanliness, organization, and adherence to shop standards during shifts.

Worked on an AI/ML-oriented large dataset for chest X-ray diagnosis classification across multiple lung diseases. Managed work timelines for timely delivery and coordinated with radiology specialists to learn diagnostic steps and differences between disease findings. Researched the domain and applied machine learning models in Python for training/testing/diagnosis with attention to accuracy. Reviewed and annotated datasets to improve algorithm performance, ensuring high-quality and consistent annotations. Participated in training and improved annotation methods and processes, selecting best approaches for specific data points and supporting project goals.