Data & Operations
Mitchell Palmer
Turning operational data into decisions and efficiency.
Data Portfolio
I help improve operations with analysis, automation, and applied modeling.
I'm Mitchell, a data professional with foundations in logistics, e-commerce, and sustainability-focused operations. I pair rigorous analysis with human-centred thinking, building automations and scientific pipelines that turn messy data into clear decisions.
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Avalanche Canada Wildfire Explorer
Interactive web application exploring wildfire perimeters within Avalanche Canada forecast regions. It includes localised and national summary statistics, plus a derived Burn Severity Patches layer using Landsat reflectance-based burn severity and a minimum patch-size threshold to highlight areas for follow-on assessment.
Climate Kegs – Carbon Neutrality Campaign
Partnering initially with Climate Neutral to measure emissions across RMU's global operations, I redirected the project into a community-driven philanthropic sustainability campaign in response to funding limitations. This led to the creation of "Climate Kegs", a tree-planting beer initiative launched in partnership with One Tree Planted.
European Alps Snowpack Depths
PostgreSQL and Python project analysing monthly snowpack trends across the European Alps using data from 2,794 weather stations. Focused on visualising seasonal changes, geographical differences, and high-elevation declines.
Salifort Motors Attrition Rates
A capstone project for the Google Advanced Data Analytics certification, this exploration investigates trends and variable associations through classification models between employee departures at the fictional Salifort Motors company.
Solar Farm Asset Performance Anomaly Detection
An AI-assisted Python project for anomaly detection across three geographically distinct solar sites, with synthetically injected fault scenarios.
Synthetic Inventory Demand Forecasting
A Python project comparing ARIMA and LSTM approaches to inventory demand forecasting - built on synthetic data to demonstrate end-to-end analytical workflow and model evaluation.