Building practical data and ML solutions for real-world systems
I design analytics workflows, machine learning experiments, and production-minded data pipelines for environmental and geospatial problems. My focus is turning noisy, high-volume data into decision-ready outputs.
About Me
I'm a data professional with a geoscience background, currently working at SeekOps in Austin, TX on methane detection and quantification workflows using UAV sensor data. My experience spans production analytics, research computing, and applied machine learning in atmospheric and geospatial domains.
At Texas A&M, I completed an MS focused on hybrid ML and data assimilation methods. Across industry and research roles, I enjoy building reliable systems that connect data engineering foundations with clear scientific and business outcomes.
Core Skills
Languages: Python, SQL, FORTRAN, JavaScript
Data & ML: pandas, NumPy, Matplotlib, reservoir computing, model evaluation
Data Engineering: ETL workflows, batch processing, reproducible analytics pipelines
Cloud & Systems: AWS EC2, Linux, cron automation, HPC environments
Domain Tools: LiDAR processing, atmospheric data analysis, environmental sensor data
Experience & Education
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Projects
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Contact Me
If you'd like to get in touch, please reach out:
Resume: Available by request via email.
📧 Email: dylanelliott@tamu.edu
💼 LinkedIn: linkedin.com/in/dylan-elliott-a44744176
🐙 GitHub: github.com/dylanelliotttamu