Ruqhaiya F. S. — Data Scientist

Hi! Thanks for checking out my profile. I’m Ruqhaiya Syeda, a data engineer and scientist with over 3 years of professional experience and ongoing research contributions in computational neuroscience. I specialize in architecting clean, reproducible data pipelines and building analytical tools that support decision-making, research, and public-sector projects. I’m actively exploring opportunities where I can combine my background in data engineering and scientific research to build meaningful, high-impact systems. Feel free to connect or reach out to collaborate at rsyeda@seattleu.edu/ ruqhaiyeahhh@gmail.com Here's a quick snapshot of my professional experience: • Developed and maintained robust ELT pipelines using Python, SQL, and DBT in production environments; applied PySpark in big data projects involving Hadoop, MapReduce, and distributed data processing. • Reduced operational load by 65% and maintenance costs by 38% while supporting ingestion across multiple business platforms at Applied Information Sciences, earning a Spot Award. • Created a custom PDF-to-vector database pipeline with Qdrant to support semantic search and internal knowledge retrieval systems. • Built production-grade neural network pipelines using TensorFlow, Keras, and LightGBM, improving ADHD classification accuracy in noisy fMRI data. • Designed interactive web applications in R Shiny and Streamlit, including a NOAA-sponsored dashboard for visualizing environmental stressor-response data. • Harmonized and automated metadata preprocessing workflows for experimental neuroscience datasets using NumPy, Pandas, and custom YAML-based config systems. • Completed hands-on implementation of Hadoop Streaming, TF-IDF computation, and Spark transformations; built MapReduce jobs to handle large-scale, irregular datasets using PySpark, Hive, and custom mappers/reducers. • Led technical integration of research outputs into publishable, visually interpretable dashboards using Plotly, SQLite, and CI/CD pipelines for reproducibility. • Experienced with Azure (Data Factory, Blob Storage, SQL DB) and AWS (EC2, S3, Lambda) for cloud-based data workflows and visualization deployment. • Familiar with DevOps tools including Git, GitHub Actions, and Azure DevOps for version control, automation, and deployment. 🏆 Highlights & Recognition • 2025 Graduate Student of the Year — Seattle University, College of Science & Engineering • Distinguished Student Award — Data Science Cohort, Class of 2025 • 5× Dean’s Honor Roll | Spot Award – AIS (GEICO) | 3rd Place – Revere XR Hackathon

Stackforce AI infers this person is a Data Engineer and Scientist specializing in Environmental Science and Computational Neuroscience.

Location: Argyle, Texas, United States

Experience: 3 yrs 2 mos