“If a picture is worth a thousand words, then a beautiful visualization is worth millions. Data analysis can be transformed into visualizations that break through the clutter and provide clear insights into stories about member experience, branch operations, and product portfolio, just to name a few. This empowers credit unions to make more informed decisions on growing their business.”
Leader, Business Solutions Team
You don’t want a data implementation partner with a checklist. You want one who is a bona fide data scientist, who marvels at the power of data science. You want Christine Schneider leading the way.
The impassioned expert behind our Business Solutions Team, Chris is all business when she’s delivering value to credit unions, but retains a bit of starry-eyed wonder when it comes to the difference data can make for her clients.
Chris oversees all elements of our delivery services, including optimization of AdvantEdge Analytics solutions to ensure that insights are captured, implemented, and delivered to credit unions.
It’s a role she spent years preparing for. Before joining our team, Chris held critical positions in finance, operations, and vendor management with CUNA Mutual Group. And before that her career included wide-ranging leadership roles in public accounting firms and the financial services industry where her responsibilities comprised operational and financial analytics, financial planning and forecasting, process improvement and resource optimization.
Chris recently earned her Master’s degree in Business Analytics from Iowa State University. She also has an undergrad degree in Accounting from the University of Northern Iowa and is a designated Certified Public Accountant (CPA).
When she’s not helping credit unions experience the wonder of data, you’ll find Chris courtside at one of her kids’ sporting events or hitting the trails with her family to relax and unplug.
Data nerd-tastic facts about Chris: Chris subscribes to—and actually reads!— the kind of data and analytics material only a data scientist could love: for example, Data Science Central, R-bloggers - -check it out to see what we mean -- and over 80+ twitter accounts specific to data and analytics.