Data & Spatial Analyst · Climate Risk Specialist
I transform complex and fragmented datasets into clear, decision-ready insights. Working at the intersection of data analytics, geospatial science, and climate risk, I combine statistical and spatial analysis, remote sensing, scenario-based modeling, and workflow automation to uncover patterns, assess risk, and communicate insights for planning, investment, and policy decisions. I leverage AI as a thought partner throughout my workstream, integrating AI-assisted development to build and optimize bespoke geospatial algorithms and automation scripts, and pursue self-directed projects exploring AI's applications within GIS and climate-risk analytics.
Turning messy, multi-source datasets into decision-ready insights with Python, SQL, and automated reporting pipelines.
↗ 02TCFD-aligned exposure assessments, hydrodynamic flood and slope-stability models across multiple climate scenarios.
↗ 03Spatial analysis, satellite-derived indices, and Google Earth Engine workflows for environmental interpretation.
↗ 04Multi-criteria decision frameworks (AHP · TOPSIS) and scenario-based exposure comparisons for planning and investment.
↗ 05Executive dashboards, technical reports, and workshops that translate model outputs into clear recommendations.
↗ 06AI as a thought partner across the workstream — building and optimizing geospatial algorithms and automation scripts, plus self-directed exploration of AI's applications in GIS and climate-risk analytics.
↗Core competencies mapped across two tracks — general data analysis and GIS/geospatial analysis — showing where the work is directly transferable versus specialized.
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| Skill area | Core tools | Data Analyst | GIS Analyst |
|---|---|---|---|
| Data analysis & statistics | Python (pandas, NumPy), SQL, exploratory & statistical analysis | ✓ | ✓ |
| Data visualization & dashboards | Tableau, Streamlit, executive reporting | ✓ | ✓ |
| Automation & scripting | Python, Bash, Selenium web scraping, workflow automation | ✓ | ✓ |
| Data QC & validation | Data cleaning, imagery / ML training-data QC, structuring | ✓ | ✓ |
| Decision & risk analytics | MCDA (AHP · TOPSIS), scenario modeling, exposure metrics | ✓ | ✓ |
| GIS & spatial analysis | QGIS, ArcGIS, spatial analysis, suitability mapping | – | ✓ |
| Remote sensing & earth observation | Google Earth Engine, satellite-derived indices, NetCDF | – | ✓ |
| Climate & hazard modeling | FLO-2D, hazard/slope-stability modeling, TCFD, RCP/SSP scenarios | – | ✓ |
| AI-assisted development | AI as workstream thought partner, AI-assisted scripting & automation, self-directed AI/GIS exploration | ✓ | ✓ |
Personal dashboard to automate exposure metrics and visualization for distributed portfolios.
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Standardized framework integrating local and global datasets for current and future scenarios.
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Mapped turbidity patterns in GEE to identify potential siltation zones.
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Hydrodynamic simulations producing flood depth and extent maps.
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Processed multi-year NetCDF datasets to detect mesoscale eddies and track lifecycle evolution.
Read case study ↗Conference presentations and research supporting multi-hazard and geospatial analytics work.
Poster presenter at GeoCon 2023 using HVSRInv (MATLAB) to estimate Vs30 for seismic hazard and site amplification, validated against Refraction Microtremor measurements.
Curated 54 cultural and historical records documenting “lost rivers” shaped by urban growth to surface links between buried waterways, flood memory, and community-led regeneration.
Geospatial framework analyzing interactions between multiple hazards, including cascading and compounding effects, supporting disaster risk assessment and resilience planning.
Remote sensing and geospatial analysis to characterize volcanic features within Benham Rise, supporting interpretation of submarine structures and regional geologic evolution.