Emma Ai
Senior Data Engineer Python Developer
Adelaide, South Australia
Summary
👤
Senior🎓
Top SchoolEmma Ai is a Senior Data Engineer and Python developer with eight years of experience building scalable data pipelines, deploying ML systems on AWS, and turning complex geospatial datasets into actionable insights. With a PhD in Mathematics and Statistics, she combines strong probabilistic modeling and research rigor with practical software engineering in Python, C/C++ and Shell. At Geoscience Australia she has led high-impact projects—contributing to the well-known dea-notebooks for Digital Earth Australia—improving geospatial metrics, interpolation and water observation workflows. Her work emphasizes computational efficiency, advanced data augmentation, and continuous model optimization to boost reliability in production. Comfortable leading agile teams, she mentors peers, drives clear technical decisions, and actively transfers knowledge across research and engineering domains. Based in Adelaide, she blends academic depth with hands-on cloud-native delivery to solve large-scale environmental data challenges.
8 years of coding experience
6 years of employment as a software developer
Australian National University
Chinese, English
Github Skills (13)
data-analysis10
satellite-imagery10
xray10
jupyter-notebook10
geospatial10
python10
spatial-data10
xa10
data-visualisation9
data-visualization9
pandas9
data-visualizations9
machine-learning8
Programming languages (9)
Github contributions (5)
GeoscienceAustralia/dea-notebooks
May 2020 - Aug 2021
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray
Role in this project:
Data Scientist
Data ScientistContributions:37 reviews, 20 commits, 38 PRs in 1 year 3 months
Contributions summary:Emma contributed to the `dea-notebooks` repository by updating and improving Jupyter notebooks focused on geospatial analysis. Their work involved modifying code related to data manipulation, visualization, and the utilization of specific geospatial libraries and packages like `dea-tools` and `xarray`. They added and improved metrics for WIT (Wetlands Insight Tool), including interpolation, and were co-authors on several commits, indicating collaboration on the project. The user also demonstrated proficiency in handling and processing geospatial data, including fractional cover and water observations.
satellite-imagerypythonjupyter-notebooklandsatearthobservation
emmaai/test_github_actions
Nov 2022 - Mar 2025
Contributions:12 releases, 78 PRs, 125 pushes in 2 years 4 months
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