Fariyab Zafar

Builds end-to-end intelligent systems. Developed SNutrify, a full-stack food recognition app where MobileNetV2 (TensorFlow Lite) handles on-device inference and the OpenAI API acts as a fallback for cases the model misses, alongside a chatbot layer for personalized nutrition guidance. Designed a normalized relational database with role-based security, concurrency control, and recovery mechanisms.

Completed a Data Analytics internship building Python preprocessing pipelines and multi-join SQL feature extraction for datasets. Works across Python, SQL, and Flutter/Dart to take projects to shipped product.

Data Analytics Intern - Elevvo Pathways - Remote

(2025-07 - 2025-08)

• Engineered Python-based data preprocessing pipelines to clean, normalize, and validate datasets across inconsistent schemas, delivering structured, ML-ready training data
• Wrote optimized multi-join SQL queries to extract, aggregate, and filter relational data, producing feature-rich datasets suitable for supervised learning model training
• Automated dataset expansion using Python web scraping and developed analytical visualizations to monitor data quality and communicate distributional findings to stakeholders
• Completed the full data lifecycle across a structured 1-month program: raw ingestion, preprocessing, validation, and analysis-ready delivery

Bachelor of Science - Information Technology - National University of Modern Languages (NUML) (2022-09 - 2026-09)