Will Beyer Email & Phone Number

Los Angeles, CA, US

• Employ advanced SQL and Python to analyze millions of monthly customer orders, crafting dynamicfraud strategies and rules ensuring continual enhancement of Klarna’s fraud prevention
• Built and maintain dashboards to visualize our KPI’s and drive strategy across all Klarna markets
• Work cross-functionally with partners in Engineering and Product Management to create the best online checkout customer experience, by communicating complex data insights in a digestible manner

Perform analytics to improve the fraud real-time decisioning of every transaction processed by Klarna in the US and Canada.

Perform data analytics in partnership with Chase for Business Marketing teams, to improve insights on campaign performance, and customer targeting and quality.

Columbus, Ohio Metropolitan Area

-Performed strategic analytics in Check and Digital fraud using SAS/SQL to improve operational efficiency, reduce the number of fraud reports, and optimize fraud alert rules-Owned the development of SAS code to analyze performance and value of 55 fraud reports in which we previously had no way of assessing value-Presented analytics findings to partners in.

Columbus, Ohio Area

• Effectively mitigated risks and advised on projects in Home Lending digital transformation, with the goal of improving the digital experience and retention of Chase customers
• Attended an intensive three day training course covering scrum/agile project execution, and applied this training to management of risk in an agile setting
• Performed an analysis of the digital competitive landscape within mortgage by researching the user experience and interface of competitor websites
• Improved the completion time of monthly data reporting by using Alteryx; a self service data analysis and coding platform

Columbus, Ohio Area

• Business Banking Risk Management
• Outlined an automated process for correcting duplicate or incorrect ID numbers for over 25,000 customers
• Analyzed customer records to identify correct ID numbers for over 4,000 customer records with duplicate records, reducing inefficiency and confusion within Business Banking
• Presented final automation project to the Chief Risk Officer of Business Banking

• Utilized R coding software to create a model predicting customer retention within the companies auto insurance product
• Analyzed a dataset of over 200,000 customer records using basic machine learning and linear regression analysis to inform the customer retention model
• Presented final predictive model to a group of company executives, displaying how certain customer characteristics affect retention and pricing strategy
• Researched pricing strategies of peer companies through rate filing analysis