Qing (Ching) L.
About Qing (Ching) L.
Qing L. is a Reporting Analyst with extensive experience in data analysis and visualization. Currently, he works at Carbon Health, where he utilizes R programming and various reporting tools to support client services.
Work at LotLinx
Qing L. has been employed at LotLinx, Inc. as a Reporting Analyst since 2015. In this role, Qing developed and maintained dashboards that present high-level results and trends to the management team. This position involves analyzing data to support decision-making processes within the organization.
Current Role at Carbon Health
Since 2021, Qing L. has served as a Senior Data Analyst at Carbon Health in Chicago, Illinois. In this capacity, Qing utilizes R programming to analyze data and derive insights that support the client service team. This role emphasizes the importance of data analysis in enhancing client interactions and service delivery.
Education and Expertise
Qing L. holds two Master of Science degrees from the Illinois Institute of Technology. The first is in Environmental Management and Sustainability, achieved from 2011 to 2013. The second is in Marketing Analytics and Communication, completed from 2012 to 2014. Additionally, Qing earned a Bachelor of Science degree in Environmental Sciences from China Agriculture University, studying from 2007 to 2011.
Previous Experience at Illinois Institute of Technology
Prior to joining LotLinx, Qing L. worked as a Student Assistant at the IIT Stuart School of Business Dean's Office from 2012 to 2015. This role provided valuable experience in an academic environment, contributing to administrative tasks and supporting the operations of the Dean's Office.
Data Analysis Skills
Qing L. has demonstrated proficiency in data analysis through various tools and programming languages. This includes querying data from MySQL and compiling information from sources such as Salesforce and Google Analytics. Qing also creates and modifies ad-hoc reports using Tableau and Google Data Studio, selecting appropriate visualizations for effective data presentation.