Courtney Youngberg · Data, Automation & Analytics

I turn messy data and manual processes into useful systems.

For over a decade, I've worked across analytics, automation, and product development, building decision-support applications, predictive models, dashboards, and Python pipelines that replace manual work. My experience spans higher education, healthcare technology, customer operations, clinical research, and public-safety data.

300+

program websites processed in PSLO automation

300+

Excel workbooks generated automatically

~2 months

of manual effort saved in one cycle

~1,600

courses in the annual DoD TA XML workflow

~70

online programs identified for institutional review

0.719

ROC AUC, interpretable retention model

• AutomationBusiness AnalysisAnalytics

  PSLO Automation System

  Institutional research, California community college

  A Python pipeline that collects and structures program learning-outcome information from 300+ program websites and generates 300+ formatted Excel workbooks. It replaced roughly two months of manual copy-paste effort and removed the anticipated need for temporary staffing.

  program websites processed

  300+ program websites processed

  Excel workbooks generated

  300+ Excel workbooks generated

  manual effort saved

  ~2 months manual effort saved

  Read the case study →

• AutomationAnalyticsData ScienceIntegration

  Certificate Eligibility Discovery Pipeline

  Retention research, Coastline College

  Scraped 500+ public program and course pages with Python and R, structured the certificate requirements, joined them against student records with SQL, and applied business-rule matching. The pipeline identified 200+ potentially eligible students and fed an operational outreach effort.

  public pages scraped

  500+ public pages scraped

  eligible students identified

  200+ eligible students identified

  Read the case study →

• Data ScienceAnalytics

  Student Success & Retention Modeling

  Retention research, Coastline College

  Built interpretable logistic-regression models to support student success and outreach work. The model reached ROC AUC ≈ 0.719 and held ROC AUC ≈ 0.679 on outreach validation, reported with limitations rather than as a magic score.

  ROC AUC

  0.719 ROC AUC (interpretable model)

  ROC AUC

  0.679 ROC AUC (outreach validation)

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• AutomationAnalyticsBusiness AnalysisIntegration

  Customer Success Technology Operations

  Tebra / Kareo · healthcare technology

  At Tebra (and previously Kareo), owned the reporting and operations tooling a CS org runs on: Snowflake SQL for customer-success metrics, Salesforce and Gainsight administration, and Jira Service Desk automation, including a ticket state machine that replaced a manual customer-outreach process with automated send, close, and reopen logic, plus a pre-payment data-quality checklist.

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