Fawzan Sayed
Data Scientist & Analyst | Researcher @ USC Viterbi | ML, AI, Data Visualization
- Role
- Research Data Scientist at Usc Viterbi School Of Engineering
- Location
- Sunnyvale, CA, US
- LinkedIn followers
- 500 followers
About Fawzan Sayed
I\'m a Data Scientist and Analyst currently pursuing my Master\'s in Applied Data Science at USC Viterbi School of Engineering, with a proven record of turning complex data into actionable insights and solutions. I specialize in building end-to-end data pipelines, advanced predictive modeling, and creating intuitive data visualizations that drive strategic decision-making. My professional experience includes: Machine Learning & AI: Developed and deployed robust predictive models (CNN, U-Net, XGBoost, LLMs) enhancing efficiency and accuracy across healthcare, research, and educational technology sectors. Data Analytics & Visualization: Created interactive dashboards and automated reporting tools (Power BI, Tableau) that significantly improved operational transparency and efficiency across university-wide systems. Software Development & Engineering: Built scalable backend services, ETL pipelines, and real-time analytics platforms using Python, Apache Airflow, AWS, and Docker, significantly enhancing system reliability, efficiency, and performance. I\'m passionate about leveraging data-driven methods to solve real-world problems, particularly in healthcare, automotive, and technology domains. Outside my professional endeavors, I\'m a motorsport enthusiast, particularly Formula racing, and always eager to explore innovative intersections between technology and automotive performance. Let\'s connect and discuss how data science and analytics can empower your organization\'s goals! Reach out: f••••••••@gmail.com | f•••••@usc.edu
Experience
Research Data Scientist
Usc Viterbi School Of Engineering
Jul 2024 — Present · Los Angeles, CA, US
Developed and deployed advanced U-Net segmentation models in TensorFlow and PyTorch for macaque brain imaging, achieving 90% accuracy and reducing processing time by 50%, enabling efficient analysis for over 500 researchers worldwide. Engineered scalable ETL workflows using Python and Apache Airflow, integrated real-time streaming with Apache Kafka, and implemented robust CI/CD pipelines (GitLab, Docker, Kubernetes) for streamlined data ingestion and model inference. Built a cloud-based data platform leveraging AWS, Apache Spark, Snowflake, DBT, and AI-driven monitoring frameworks (Prometheus, Grafana), ensuring high data integrity and reliable analytics.
Education
Dwarkadas J. Sanghvi College of Engineering
Bachelor of Engineering - BE
2018 — 2022
University of Southern California
Master of Science - MS
2022 — 2024
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