H1B Visa Data Analysis: Unveiling patterns of H1B Visa Approval

H1B Visa DataThe H1B visa program has long been a gateway for skilled professionals worldwide to bring their expertise to the United States, fostering innovation and growth in various industries.

In this article, we embark on a data transformation journey to explore and analyze H1B visa data from the Office of Foreign Labor Certification (OFLC).

By using meticulous data wrangling and feature engineering techniques, we gain valuable insights from the dataset spanning the years 2014 to 2016.

 

 

Data Preprocessing

To begin our analysis, we transform the provided xlsx file to CSV format, standardize column names across the three years of data, and merge them into a comprehensive dataset comprising 1,786,160 rows and 17 columns. By creating an employment period column based on start and end dates, we facilitate a deeper understanding of visa tenure and its implications.

Feature Engineering

Enhancing the dataset further, we calculate the duration of employment in days and convert it to months, eliminating logically impossible negative values. Missing data is addressed by replacing null entries with zeros. Additionally, we determine the sector of each employer by extracting the first two digits from the NAICS code and mapping them to the corresponding sector using external data sources. This enriched dataset now includes a dedicated year column, simplifying year-based insights.

Data Transformation

To refine the dataset, we remove duplicate records, preprocess the LCA_CASE_SOC_CODE column by removing special characters, and impute missing values in the LCA_CASE_SOC_NAME column using data scraped from “https://www.bls.gov/oes/current/oes_stru.htm#29-0000“. Furthermore, we standardize the wage rates in the ‘LCA_CASE_WAGE_RATE_FROM’ column to a uniform annual value, allowing meaningful comparisons across positions and categories.

Analysis

  • Total Number of H-1B Visa Applications and Growth Rate Between 2014 and 2015, H1B visa applications witnessed an astounding 17.7% growth, followed by a 9% drop in 2016. To identify the cause of this decline, we examined rejection rates, which surprisingly decreased from 5.41% to 3.4% over the years. This reduction suggests a more favorable environment for visa applicants, indicating other factors contributed to the decrease in application numbers.
  • Top Sectors for H1B Visa Applications Approximately 72.4% of H1B visa applications were concentrated in the professional, scientific, and technical services sectors. This demand highlights the need for skilled professionals in various fields, including computer programming, scientific research, engineering, and consulting services.
  • Top 10 Employers and Their Impact on Job Positions The professional, scientific, and technical services sectors dominated the top 10 employers list, with Infosys leading the way with 82,271 approved applications. The influence of these top employers on specific job positions is significant, with each contributing to the success of particular roles.
  • Salary Range and its Impact on Visa Decisions Surprisingly, we found no substantial correlation between the salary range and the application status. Both accepted and denied applications showed similar salary ranges, indicating that other factors played a pivotal role in the visa decision-making process.
  • Employment Period and its Influence on Visa Decisions Similar to the salary range, the duration of employment had no substantial impact on visa decisions. The employment period’s lack of correlation with application status implies that other variables influenced the outcomes.
  • Geographic Distribution of H1B Visa Workers Texas, California, and New Jersey emerged as top states for H1B visa applications, suggesting a heightened demand for skilled professionals in these regions.

Other Observations

This comprehensive analysis of H1B visa data from 2014 to 2016 provided valuable insights into the trends and patterns surrounding the visa program. While the total number of H1B visa applications saw significant growth in 2015, it declined in 2016 despite a reduction in rejection rates. This suggests that factors other than visa approval rates influenced the decrease in applications.

The professional, scientific, and technical services sectors emerged as the top employers seeking H1B visas, indicating a strong demand for skilled professionals in fields such as computer programming, scientific research, engineering, and consulting services. Among the top 10 employers, Infosys stood out with the highest number of approved applications, highlighting its impact on the job market for skilled foreign workers.

Interestingly, the salary range and employment period did not show significant correlations with visa application outcomes. This implies that the decision-making process for H1B visas considers various factors beyond just salary and job duration. Other elements, such as job specialization, employer reputation, and visa category, might have influenced visa decisions.

The geographic distribution of H1B visa workers showed that Texas, California, and New Jersey were the top states with the highest demand for skilled foreign workers. These states likely had vibrant economies and industries requiring specialized talent from abroad.

While this analysis provides valuable insights into the H1B visa program’s dynamics, there are limitations to be acknowledged. The dataset only covers a three-year period, which might not fully capture longer-term trends. Additionally, the dataset’s focus is on approved applications, limiting insights into the reasons for denials and the overall competitiveness of the program.

For future research, it would be beneficial to expand the analysis to include more recent data, if available, and to explore the factors contributing to visa denials. Understanding the reasons behind visa denials can provide crucial information for applicants and employers to improve their chances of success.

Moreover, policymakers can use the insights from this analysis to assess the program’s effectiveness and identify areas for improvement. For instance, if certain sectors consistently face challenges in obtaining visas, targeted policy changes or support measures could be implemented to address the issue.

Conclusion

The H1B visa program continues to play a pivotal role in attracting skilled foreign workers to contribute to the United States’ economic growth and innovation.

Through data analysis and informed decision-making, stakeholders can work towards a more efficient and inclusive H1B visa program that benefits both skilled foreign workers and the country as a whole.

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