Dania Waseem

Data Science graduate with a strong foundation in machine learning, deep learning, and NLP. Experienced in building end-to-end data pipelines, statistical modelling, and deploying ML models for real-world applications including multimodal deep learning, transformer-based NLP, and large language model evaluation. Passionate about uncovering meaningful insights from complex datasets and developing robust, data-driven solutions across diverse domains.

Research & Development Intern (Summer Internship) at AIMS Lab (2025-06 – 2025-08)

• Engineered a multimodal deep learning pipeline for automated football highlight detection, achieving 83.3% event detection accuracy across 500+ annotated clips.
• Benchmarked multimodal late-fusion architecture against audio-only and video-only baselines; multimodal approach outperformed single-modality models by 12+ percentage points.

Research Intern (Remote) at Omega Accountants Ltd, UK (2025-06 – 2025-08)

• Researched fintech and cryptocurrency regulatory frameworks across UK and Pakistan markets, producing structured analytical reports for stakeholder review.
• Contributed to UI/UX design workflows and software documentation in a cross-border remote environment.

Teacher Assistant & Lab Expert at FAST-NUCES, Islamabad (2025-01 – Present)

• Guided 50+ students per semester through lab sessions, Proteus-based hardware testing, and coursework evaluation.
• Conducted weekly office hours reinforcing concepts in digital circuits, formal logic, and relational database design.

BS in Data Science – FAST-NUCES, Islamabad (2023 – 2027)

Advanced Subsidiary Level (AS Levels) in Pre-Engineering – Longley Park Sixth Form, Sheffield, UK (2021 – 2022)

Advanced Level (A Levels) in Pre-Engineering – SuperNova College, F-8/1, Islamabad (2022 – 2023)

IGCSE (O Levels) in Sciences – SuperNova School, F-8/1, Islamabad (2019 – 2021)