Creating a Data Visualization to Search for H-1B Visa Employers

H-1B applications visualized by companies, job titles, and salary.

Summary

THE PROBLEM

The US Citizen and Immigration Services (USCIS) offers a data set about H-1B visa case submissions, however, this data is often displayed in a text or table format that results in 3 problems: difficult to quickly understand, identify trends, and personalize a search.

OUR SOLUTION

Synthesizing the massive dataset into a more readily understandable, personalizeable, and cohesive set of interactive visualizations with the aim of helping inform internationals who seek U.S. employment through the H-1B visa sponsorship program.

MY ROLE

UX Researcher who developed the research strategy that included 1 online survey, 7 usability test sessions, and an analysis of our results used to direct design iterations.

TOOLS

Tableau, R, Excel

Data Preparation

Data Source: Office of Foreign Labor Certification 

We used ~600,000 data points that covered variables/fields such as target employer, prevailing wage, starting salary, city, application date, etc., covering a complete history of H-1B visa applications between October 1, 2016 and September 30, 2017.

R was used to understand, clean, and process the relevant dimensions used for the visualizations.

Our talented data scientist, Rahul, did most of the data processing.

Survey

Purpose: Understand the challenges, goals, and perceptions of target users regarding H-1B applications.

Participants: International citizens planning to apply for H-1B sponsorship. 

Findings: 

• Participants do not know which employers have experience sponsoring H-1B.
• Participants want to know approval ratings by employer.
• Participants are interested in H-1B in H-1B case submission and approvals by job title. 
• Participants fear that needing an H-1B visa will affect employability.