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Data enthusiast with 6+ years of experience in developing data solutions supporting analysis, reporting and predictive modeling. Proven ability to design and maintain a data warehouse that enables scalable analysis. Master’s degree in Data Science and developed 5+ predictive models through to production. Passionate about efficiencies in database & query design and exploring new techniques/products.


Work Experience

Data Modeling Manager

Vervent Card | Sept 2021 - Present

Started an internship at Vervent Card during grad school and continued as an analyst fulltime after completing school. Managed a 30TB SQL Server data warehouse for the rapidly expanding data science division, which more than tripled in size during tenure. Acted as primary subject matter expert for data used by the data science division.

  • Migrated analytic processes, reporting and models onto a dedicated server to reduce resource impact on production, without gaps in operational availability.
  • Implemented PowerBI reporting framework and associated data structures while migrating hundreds of legacy SSRS reports.
  • Deployed predictive models into production and built structures to track performance

Credit Risk Intern/Analyst/Senior

Total Card Inc. | 2018 - 2021

Production Operator

Larson | 2014 - 2017

Yard Landscaper

Q Mowing | 2008 - 2015

Education & certificates

Master of Science Data Science

2018 - 2019

  South Dakata State University

Bachelor of Science Mathematics

2014 - 2017

  South Dakata State University
  Minors: Accounting & Stats

Azure Data Fundamentals DP-900

2024

  Microsoft - 5CEB70688A0588BB

Projects

Car Data Scraping & Analysis

SQL ETL Python

Scraped car sales data on multiple makes, models, & years from Edmunds. Collected with python and cleaned the data into SQL Server. Built infastructure to store periodic data scrapes to update and log new cars by VIN.

NCAA March Madness Modeling

RStudio Regression

This project was to create the best possible March Madness bracket score. Multiple different decision tree regression methods such as Random Forest, Boosting, & Bagging were used. Final RF model placed in the 95th percentile of 3 million ESPN brackets.

Auto App Submit Testing

Python Selenium

A selenium app to submit an application in an automated method. This is the proof of concept version I built personally and brought to my job to start automating website & underwriting testing. Completes a web app with stored values and stores outcome data, screenshots, and pdf.