Automation
Two workflows I rebuilt.
At Parkalytics, I worked on the systems behind drone-based parking studies: planning surveys, processing aerial imagery, validating model outputs, supporting geospatial analysis, and removing repetitive work with Python.
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Automation Less manual work more time for higher-value decisions
01 / Python automation
Recurring research, handled automatically.
I built an internal Python tool that turned a recurring manual research process into consistent, decision-ready reporting. It reduced administrative overhead and gave the team more time to act on relevant opportunities.
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Geospatial workflow Faster analysis consistent results at a larger scale
02 / Geospatial analysis
Complex analysis, made repeatable.
I developed an internal geospatial workflow that accelerated complex proposal analysis and standardized how results were produced. The team could evaluate larger areas through a faster, more consistent process.
Survey operations
From flight plan to validated output.
Before a survey, I created drone flight plans, reviewed airspace restrictions, researched sites with Google Maps, and mapped the survey regions in QGIS.
After collection, I processed aerial imagery through AWS EC2, ran the vehicle-detection pipeline, and validated the model outputs.
Flight planning / Airspace review / AWS EC2 / ML inference / Output validation / QGIS
Internal processes
Work the next intern can repeat.
I turned the workflows I used into onboarding guides, training videos, and project tracking systems so future interns could pick them up quickly.
- 01Onboarding guides
- 02Training videos
- 03Project tracking systems
Role progression
I continued after the co-op.
After completing the summer term, I continued part-time in September 2026 as Data & Operations Analyst.
- Current / Part-time Data & Operations Analyst to present
- Co-op Data & Operations Analyst to
Working with
Python / AWS EC2 / QGIS / Excel / Google Maps / ML inference / Aerial imagery