Soren DeOrlow

Theme

Data, Models & Decisions

From exploratory notebooks to business decisions.

This theme gathers the work where I moved back and forth between data and decision. It includes the Machine Intelligence coursework at USC (IDSN 599), marketing analytics with k-means customer segmentation (MKT 566), data-warehousing and BI pipelines (DSO 528), data-science at scale (DSCI 550), and the statistical foundations I built with Stanford’s online Statistics course and the INSPIRIT AI Fellowship.

The through-line is honest interpretation: when the data supports a decision, when it doesn’t, and how to write the uncertainty into the recommendation rather than out of it.

Essays

Prototypes

  • USDA Food Access Research Atlas — North County San Diego

    Analyzing food-desert conditions in San Diego's North County by comparing USDA census-tract data from 2015 and 2019 — tracking shifts in poverty, SNAP enrollment, and demographic composition across 72,864 tracts.

  • Peloton Customer Churn Analysis

    Investigating why Peloton customers reduce usage — combining 273 survey responses with geocoding (GeoPy) and U.S. Census demographics to surface churn patterns across age, income, and geography.