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On May 02 there were 147024 job postings open in the state of Texas. On June 02 there were 155582 job postings open in the state of Texas. The state of Texas experienced a 6% percent change in the number of total job postings open. The Dallas/Fort Worth region experienced the highest number of job postings open as of May 02 , and Dallas/Fort Worth region experienced the highest number of job postings open as of June 02 . San Angelo experienced the largest change in job postings over the May 2020 to June 02 time period .

The job postings open in the following Texas regions are outlined below:

Abilene : 38% change in job postings ( From 1295 openings on May 02 to 1788 openings on June 02 )
Amarillo : 14% change in job postings ( From 1850 openings on May 02 to 2110 openings on June 02 )
Austin : 25% change in job postings ( From 4848 openings on May 02 to 6049 openings on June 02 )
Beaumont : 29% change in job postings ( From 1658 openings on May 02 to 2131 openings on June 02 )
Bryan : 21% change in job postings ( From 1521 openings on May 02 to 1847 openings on June 02 )
Corpus Christi : -5% change in job postings ( From 5710 openings on May 02 to 5407 openings on June 02 )
Dallas/Fort Worth : 1% change in job postings ( From 43466 openings on May 02 to 44069 openings on June 02 )
Del Rio/Eagle Pass : 12% change in job postings ( From 284 openings on May 02 to 317 openings on June 02 )
El Paso : -18% change in job postings ( From 7671 openings on May 02 to 6307 openings on June 02 )
Houston/Galveston : 8% change in job postings ( From 39066 openings on May 02 to 42071 openings on June 02 )
Laredo : -16% change in job postings ( From 2465 openings on May 02 to 2065 openings on June 02 )
Lubbock : -3% change in job postings ( From 4358 openings on May 02 to 4216 openings on June 02 )
Lufkin/Nacogdoches : 16% change in job postings ( From 709 openings on May 02 to 825 openings on June 02 )
McAllen/Brownsville : 16% change in job postings ( From 1304 openings on May 02 to 1519 openings on June 02 )
Midland/Odessa : 14% change in job postings ( From 2496 openings on May 02 to 2856 openings on June 02 )
San Angelo : 44% change in job postings ( From 256 openings on May 02 to 369 openings on June 02 )
San Antonio : 8% change in job postings ( From 21012 openings on May 02 to 22788 openings on June 02 )
Sherman/Denison : 32% change in job postings ( From 699 openings on May 02 to 925 openings on June 02 )
Texarkana : 24% change in job postings ( From 821 openings on May 02 to 1016 openings on June 02 )
Tyler/Longview : 30% change in job postings ( From 2374 openings on May 02 to 3077 openings on June 02 )
Victoria : 30% change in job postings ( From 423 openings on May 02 to 548 openings on June 02 )
Waco/Temple/Killeen : 23% change in job postings ( From 1921 openings on May 02 to 2358 openings on June 02 )
Wichita Falls : 13% change in job postings ( From 817 openings on May 02 to 924 openings on June 02 )

For May 2020 in the state of Texas, Languageline Solutions posted the largest number of job openings in the state of Texas, with 1157 openings, followed by Walmart / Sam s (with 1025 openings) and USAA (with 723 openings). In total, these employers posted 2905 new job openings this month in Texas. Last month, Languageline Solutions , Walmart / Sam s , and Christus Health had the largest number of job openings in Texas.

The largest share of these job openings were in the San Antonio area.
These different employers each had their own demands for employees from a variety of occupations. For example, Languageline Solutions were, in particular seeking qualified Interpreters and Translators , with over 1156 job postings this month. For Walmart / Sam s , Training/Development Specialists were in high demand, with over 180 job postings this month. And at USAA , Financial Specialists, NEC were in high demand, with over 129 job postings this month.

For the month of May 2020 employers in the Dallas/Fort Worth metropolitan area posted the highest number of new job openings in the state of Texas. In the last month, there have been 42000 job postings in the Dallas/Fort Worth metropolitian area. Houston/Galveston reported the second highest number of job openings in Texas, with 39162 job postings this month.

In the Dallas/Fort Worth area, Software Developers, Application were the most widely sought after positions by prospective employers, with a total of 3027 job positings this month. The other job positions that experienced the highest demand this month in the Dallas/Fort Worth area were Computer Occupations, All Other with 2123 job postings, and Sales Reps, Exc Tech/Sci Product with 1617 openings.

In May 2020 Registered Nurses are in high demand in Texas, with 6275 openings, the largest number of active job openings. Other occupations in high demand include Software Developers, Application , with 5903 active openings, and Sales Reps, Exc Tech/Sci Product , with 4973 active openings. Last Month, April 2020 , the jobs with the largest number of openings were Registered Nurses , Sales Reps, Exc Tech/Sci Product , and Software Developers, Application .

May saw increased demand for Driver/Sales Workers with the largest number of new job postings by prospective employers, over 350 in the past few weeks. Middle School Teachers also saw large increases in openings, with 225 new posted positions, followed by Elementary School Teachers with 169 new posted positions within the past few weeks.

On April 01 there were 166718 job postings open in the state of Texas. On May 01 there were 146510 job postings open in the state of Texas. The state of Texas experienced a -12% percent change in the number of total job postings open. The Dallas/Fort Worth region experienced the highest number of job postings open as of April 01 , and Dallas/Fort Worth region experienced the highest number of job postings open as of May 01 . Laredo experienced the largest change in job postings over the April 2020 to May 01 time period .

The job postings open in the following Texas regions are outlined below:

Abilene : 0% change in job postings ( From 1264 openings on April 01 to 1262 openings on May 01 )
Amarillo : -10% change in job postings ( From 2051 openings on April 01 to 1838 openings on May 01 )
Austin : -3% change in job postings ( From 4932 openings on April 01 to 4801 openings on May 01 )
Beaumont : -24% change in job postings ( From 2150 openings on April 01 to 1638 openings on May 01 )
Bryan : -28% change in job postings ( From 2115 openings on April 01 to 1515 openings on May 01 )
Corpus Christi : -15% change in job postings ( From 6855 openings on April 01 to 5808 openings on May 01 )
Dallas/Fort Worth : -18% change in job postings ( From 53162 openings on April 01 to 43326 openings on May 01 )
Del Rio/Eagle Pass : -9% change in job postings ( From 309 openings on April 01 to 282 openings on May 01 )
El Paso : -9% change in job postings ( From 8574 openings on April 01 to 7780 openings on May 01 )
Houston/Galveston : -5% change in job postings ( From 40943 openings on April 01 to 38848 openings on May 01 )
Laredo : 13% change in job postings ( From 2203 openings on April 01 to 2496 openings on May 01 )
Lubbock : -10% change in job postings ( From 4865 openings on April 01 to 4400 openings on May 01 )
Lufkin/Nacogdoches : -16% change in job postings ( From 865 openings on April 01 to 727 openings on May 01 )
McAllen/Brownsville : -9% change in job postings ( From 1425 openings on April 01 to 1296 openings on May 01 )
Midland/Odessa : -20% change in job postings ( From 3117 openings on April 01 to 2503 openings on May 01 )
San Angelo : -28% change in job postings ( From 351 openings on April 01 to 253 openings on May 01 )
San Antonio : -15% change in job postings ( From 24339 openings on April 01 to 20746 openings on May 01 )
Sherman/Denison : 5% change in job postings ( From 643 openings on April 01 to 675 openings on May 01 )
Texarkana : -4% change in job postings ( From 842 openings on April 01 to 811 openings on May 01 )
Tyler/Longview : 0% change in job postings ( From 2344 openings on April 01 to 2339 openings on May 01 )
Victoria : -15% change in job postings ( From 496 openings on April 01 to 423 openings on May 01 )
Waco/Temple/Killeen : -9% change in job postings ( From 2109 openings on April 01 to 1929 openings on May 01 )
Wichita Falls : 7% change in job postings ( From 764 openings on April 01 to 814 openings on May 01 )

For data-based evidence, the analysis is the heart of the content: the output of the data compiled for a case. In most instances, the analytics do not need to be complex. Indeed, powerful results can be derived by simply calculating summary statistics (mean, median, standard deviation). More complicated techniques, like regressions, time-series models, and pattern analyses, do require a background in statistics and coding languages. But even the most robust results are ineffective if an opposing witness successfully argues they are immaterial to the case. Whether simple or complex, litigants and expert witnesses should ensure an analysis is both relevant and robust against criticism.

What type of result would provide evidence of a party’s assertion? The admissibility and validity of statistical evidence varies by jurisdiction. In general, data-based evidence should be as straightforward as possible; more complex models should only be used when necessary. Superfluous analytics are distractions, leading to expert witnesses “boiling the ocean” in search of additional evidence. Additionally, courts still approach statistical techniques with some skepticism, despite their acceptance in other fields.

If more complex techniques are necessary, like regressions, litigants must be confident in their methods. For example, what kind of regression will be used? Which variables are “relevant” as inputs? What is the output, and how does it relate to a party’s assertion of fact? Parties need to link outputs, big or small, to a “therefore” moment: “the analysis gave us a result, therefore it is proof of our assertion in the following ways.” Importantly, this refocuses the judge or jury’s attention to the relevance of the output, rather than its complex derivation.

Does the analysis match the scope of the complaint or a fact in dispute? Is the certified class all employees, or just a subset of in a company? Is the location a state, or a county within a state? If the defendant is accused of committing fraud, for how many years? Generalizing from a smaller or tangential analysis is inherently risky, and an easy target for opposing witnesses. If given a choice, avoid conjecture. Do not assume that an analysis in one area, for one class, or for one time automatically applies to another.

A key component of analytical and statistical work is replicability. In fields such as finance, insurance, or large scale employment cases, the analysis of both parties should be replicable. Outside parties should be able to analyze the same data and obtain the same results. In addition, replicability can expose error, slights of hand, or outright manipulation.

Data-based evidence requires focus, clarity, and appropriate analytical techniques, otherwise an output is just another number.

EmployStats is sponsoring a CLE seminar on Data Analytics in Complex Litigation at the University of Baltimore in the Merrick School of Business on April 5, 2019 from 9:30AM to 1:30PM. Complex litigation entails an enormous amount of data, which may appear impossible to sort or manage. This CLE seminar is all about how large datasets are analyzed in litigation.

The Merrick School of Business is located in the Mt. Vernon neighborhood of midtown Baltimore. Attendees are within walking distance of nearby Penn Station and a number of museums and restaurants.

Attendees will receive complementary breakfast and lunch, and hear from our accredited speakers: Roberto Cavazos, Ph.D., Kyle Cheek, Ph.D., Dwight Steward, Ph.D., and Vince McKnight. Our speakers have performed analytics work for top law firms and multinational companies across industries. Our speakers will be covering a wide range of issues on Data Analytics, and how its tools are applicable across the legal profession.

Looking to enroll? Visit: https://www.bigdatacleseminar.com/

The enormous volumes of data generated by organizations will typically outgrow its infrastructure. Changes in an organization’s work flow affect data in a variety of ways, which in turn affect the use of internal data as evidence in litigation.

Often data is transformed to ensure different systems exchange, interpret, and use data cohesively in an organization. Data integration and interoperability are complex challenges for organizations deploying big data architectures, as data is heterogeneous by nature. Thus, siloed storage emerge from different demands and specifications from different departments. Legacy data, which may have been administratively useful previously, is stored, replaced, and frequently lost in the transition. All of this helps explain why roughly two-thirds of electronic data collected by organizations go unused. Constant demands to reconfigure data processes, structures, and architecture carry significant risks for organizations, as these demands outpace administrative protocols and laws.

Properly integrating different data sources for an analysis involves an awareness of all these technical complications.

Once potential data sources are identified for an analysis, the next step is inspect the variables which will be integrated. Knowing exactly what each variable means may involve additional questions and scrutiny, but it is an important step. In a given dataset, what is defined as “earnings”? What are all the potential values for a “location” variable? Are certain sensitive values, like a user’s social security number, masked to ensure privacy? Variables are also defined by a class, or acceptable input value. In one table, a given date may be stored in as a datetime class, while another may store the same value as a character string.

Having confidence in the variables’ meanings will reflect in the confidence of an analysis, and ultimately the presentation of evidence in court. A party bears additional risks if its expert witnesses are unable to explain the ‘real meaning’ of a value under scrutiny.

A party also needs to know how potential variables will merge datasets. Merging data within a database is easy done with primary keys, whereas merges between two different structured sources requires more effort. How many common variables are necessary when merging two sources to prevent the deletion of similar values? How much overlap between variables will yield an acceptable size data set? These factors affect the final output. Faulty mergers, null values, and accidental data removals cost time and resources to resolve.

There are various methods to extract, transform, and load disparate data into a unified schema. For simplicity, the ideal scenario should be to merging and aggregating the necessary inputs into the fewest datasets possible. Massive tables outweigh the difficulty of analyzing scattered sources and proving their relevance as a whole. Proper data integration will reveal whether a litigant’s data is a gold mine or a time bomb.

David Neumark is an American economist and a Chancellor’s Professor of Economics at the University of California, Irvine, where he also directs the Economic Self-Sufficiency Policy Research Institute. Professor Neumark graduated with a B.A. in economics in 1982 from the University of Pennsylvania. He graduated Phi Beta Kappa, Summa Cum Laude, with Honors. He went on to complete his M.A. in 1985 and Ph.D. in 1987 in economics from Harvard University. His fields were labor economics and econometrics. His dissertation was entitled Male-Female Differentials in the Labor Force: Measurement, Causes and Probes, and published in parts in the Journal of Human Resources.  Professor Neumark’s research interests include minimum wages and living wages, affirmative action, sex differences in labor markets, the economics of aging, and school-to-work programs, and has also done work in demography, health economics, development, industrial organization, and finance.

Professor Neumark is an academic affiliate at EmployStats and will be a speaker at the employment CLE sponsored by EmployStats on July 12, 2017 in San Francisco.  Professor Neumark is a renown labor economist who has performed extensive research on wage disparity related issues, and has extensive knowledge into the current California Fair Pay Act and its implications in the labor force.  He and Dr. Dwight Steward will hold a discussion on the statistical implications of the California Fair Pay Act and the use of statistics in recent cases.

For more information on speakers and registration for the July 12, 2017 CLE, please visit: www.californiaequalpay2017cle.com/

Lori Andrus, of Andrus Anderson LLP, specializes in class actions and complex litigation. She represents female employees who are paid less than their male counterparts, and individuals who have been harmed by dangerous pharmaceuticals or medical devices, been defrauded by large corporations or sold defective products. Lori Andrus has received Martindale-Hubbell’s highest rating (AV) for legal ability and ethical standards, and has been recognized as a “Top 50” Northern California Super Lawyer in 2016. In 2015, the National Law Journal named her as one of the nation’s 75 “Outstanding Women Lawyers.”

Lori Andrus, most notably, was instrumental in negotiating a cutting edge settlement with Farmers Insurance on behalf of their female attorney employees who alleged they were paid less than their male counterparts doing the same work.  Lori’s extensive experience litigating class action, with specific focus involving the California Equal Pay Act, will be a great addition to our employment CLE sponsored by EmployStats on July 12, 2017 in San Francisco.  

Register here to learn from Lori Andrus first-hand: www.californiaequalpay2017cle.com