Data Science And The Pay Gaps Plus New Laws On The BooksNov 28, 2022
Will Pay Transparency Laws in New York and California Do Enough to Eliminate the Pay Gap?
Data Science is a field that both perpetuates gender and racial pay gaps and also that offers solutions to reducing gender and racial pay gaps. In order to create a more equitable place for women and all races in the field of data science, there must be equal pay for equal work. It is important that these efforts not only focus on gender but also on race as well so that we can truly prioritize equity for all people.
California and New York are now two of the only four states that currently have pay transparency laws. According to the Pew Research Center, women earn, on average, 84 percent of men’s wages for the same role. Researchers also observe these pay gaps in regional data. For example the Boston Women’s Workforce Council recently found women in the Boston area were seeing 70 cents for every dollar earned by men.
The Pew Research Center also reports that average hourly wages for Black and Latino men lag behind the hourly pay of white men. Further, the U.S. Census Bureau reports that the wage gap for women of color is even more significant than that of white women.
Pay transparency laws intend to address this disparity and maybe data science can help.
What the New Laws Do
Knowing what the pay transparency laws in California and New York require is crucial to reap the benefits. It is not yet clear how well enforcement will succeed. Some businesses may need regulatory accountability. Here is how the new laws change the landscape for job seekers and current employees looking for career advancement.
With California’s high concentration of tech companies (including a massive collection of professionals in data science, machine learning, artificial intelligence, and advanced analytics) it is possible that tech professionals will be among those that best reap specific pay transparency legal benefits. While California already had some regulations in place meant to target pay gaps, the new law broadens the scope and requirements for employers in the state.
In California, companies with at least 15 employees are now required to include a pay scale in their job listings. This measure allows job seekers and current employees seeking promotional opportunities to learn about pay before applying for new positions.
Larger companies with at least 100 employees are required to create a pay data report each year and submit it to the Department of Fair Employment and Housing. One of the brightest spots in this legislation is the requirement for disaggregated (or segmented) data. For example, these reports must include each position’s mean and median pay details for sex, ethnicity, and race.
Penalties for violating the reporting requirement in the new law are minimal and not likely to inspire compliance from every employer. Companies will be fined a mere $100 for each employee omitted from the annual report. Some companies might just choose to pay the fines as a cost of business.
As of November 1, 2022, New York requires companies to list minimum and maximum wages in their job postings. In addition, the posted hourly wage or annual salary must represent a good faith estimate or range that the employer legitimately feels they are willing to pay an employee for that role. Notice the subtle choice of language regulators and statutory drafters chose when writing this requirement.
In some ways, New York’s pay transparency law has stricter rules than California’s. The penalties for not complying are harsher in New York. Any company with four or more employees is required to comply with New York’s new law. Further, owners of the business count toward this total. Fines for noncompliance can reach $250,000 .
Data Science Can Help & More Work to Do
State legislation and government oversight are good first steps toward equal pay and inclusivity. Creating a foundation that supports pay transparency will move the needle in the right direction and make efforts toward wage equality more commonplace. However, forced inclusion and transparency can only go so far. Significant reductions in the wage gap may require companies to undergo a cultural shift that allows them to revise their core policies in more equitable ways.
An example of a meaningful cultural shift would be implementing regular equity audits which employ new, innovative, critical, and revealing insights. The goal is for companies who are dedicated to reducing wage and pay gaps to bring new tools and a new vigor to the work. Another potential solution is for organizations to partner with outside organizations. By allowing external organizations to review pay and wage equity, there may be an added measure of accountability and objectivity.
Because data science is a multi-disciplinary field and because pay and wage disparity is a inter-disciplinary problem it seems natural to include data scientists in the mix of professionals who can better understand and solve this problem. By bringing together our different strengths in the field of data science and by encouraging a culture of openness and collaboration, we can begin eliminating pay gaps.
For Those Transitioning Into Data Science
Most of those who are in the process of a career transition or those interested in career advancement value transparency from their current or potential employers. Companies should see these new regulations as a win-win – if done well, compliance with these laws will attract higher quality and more engaged candidates. Employer transparency breeds an environment of trust, which is a valuable tool in creating a healthy company culture. Employees who feel informed, involved, and respected perform better.
Some companies, who provide data science consulting might even find opportunities for business development here. Less data-savvy and less tech-savvy employers will need help from consultants who can help understand and solve this problem. In other words, equity also makes for a business opportunity.
Above And Beyond
There are specific and measurable reasons employers should go above and beyond the California and New York requirements. As demonstrated by research from Tel Aviv University, pay secrecy reduces employee performance. This experiment divided student workers into two groups. According to the study protocol, one group of employees could discuss pay. The other group could not to discuss pay. The group of student workers that had been allowed to discuss pay outperformed the group that had not been allowed to discuss pay .
A study done by Emiliano Huet-Vaughn, a professor at Middlebury College during his doctoral program at the University of California - Berkeley, gave students money in return for data entry work. The people taking part in the study did the tasks over two rounds. At the finish of the first round, one group was given information on how much they earned and their performance. The other group was not given any information about how much money they could make or their level of performance. The study showed that in the second round of data entry, the group with this type of information performed better than those without it. Therefore, when workers can see that their pay is based on how well they do their job, it gives them an incentive to work harder and earn more money .
In general, employers who offer complete pay transparency have had positive feedback from their workers. So-called “complete pay transparency” is not a small commitment. Complete pay transparency means that no salary or pay rate is private, including that of upper management and C-Suite executives. This particular method does a lot to inspire upward movement and career advancement goals for employees, as they see what their pay could be if they work toward promotional opportunities within the company.
As discussed above, employers focused on taking a proactive approach to eliminate the pay gap can use data science to their advantage by compiling their own data for in-house pay analysis. Each employee’s pay rate compared to the disaggregated mean and medians by gender, race, and ethnicity can work to identify any unintentional or intentional bias. To go another step further, companies can also analyze age and disability status data, as ageism and ableism can contribute to pay disparity, too.
Salary and hourly rates should reflect the scope and market value of the position, which eliminates subjective determinants of pay. By using an objective measure, companies can ensure that each employee receives a fair salary. Additionally, this method means that businesses can provide a clear and unbiased explanation of how they determine the pay rate for each person. Thus, employees with high performance receive increased responsibilities and more tasks, leading to career advancement and higher pay.
Researching and Negotiating Your Salary
Another important benefit these new laws bring workers, is that they offer a new source of open and free compensation intelligence. Compensation intelligence is information related to what your employer, and other employers, pay for the kind of work that you perform.
Even armed with the knowledge of these new laws involving pay transparency, salary negotiations and discussions can be intimidating. As a professional career counselor, I show my clients how to approach these conversations with confidence. While my specific expertise involves topics in data science, machine learning, and artificial intelligence, my ability to help people prepare for career transitions and advancements is not limited to the technology or data industries.
In previous articles, I’ve written about ways to revolutionize your salary research, why employers should pay their interns, and how to prepare for salary negotiations, with a specific article dedicated to data scientists.
This article reviewed five important points for data scientists, and other tech workers, to know about the new string of pay and wage transparency laws that have recently gone into effect. First, this article discussed what the laws do. Second, what these laws might mean for those transitioning into the field of data science. Third, this article also discussed the benefits of going above and beyond the minimum legal requirements and also how data science can help employers strive for those higher standards. Lastly this article offered a reminder that these new laws mean candidates will have a new source of salary and compensation intelligence.
I am hopeful that the new laws in California and New York will diminish the pay gap, but I do not believe this is the final step. There is more to do. Pay transparency laws lay the groundwork for more inclusivity. The new laws may inspire change on a level that will creates meaningful advances in equality. But there is more to do. Until then, I help my clients understand how to make the most of these new laws for their own career development and advancement.
 NYC Commission on Human Rights. Salary Transparency in Job Advertisements. https://www1.nyc.gov/assets/cchr/downloads/pdf/publications/Salary-Transparency-Factsheet.pdf
 Belogolovsky, E., & Bamberger, P. A. (2014). Signaling in secret: Pay for performance and the incentive and sorting effects of pay secrecy. Academy of Management Journal, 57(6), 1706–1733.
 Huet-Vaughn, E. (2013). Striving for status: A field experiment on relative earnings and labor supply. Job Market Paper, UC Berkeley.