Thread regarding Cisco Systems Inc. layoffs

@nq i know but they will be eligible for high speed Green Card processing and will always hire their kind no matter what, and promote their kind on cooperate ladder. Seems like whatever LR they did recently got replaced with these folks.

@et these are low numbers for a director i think RSUs are not included in their numbers and hence its skewed

@jy replacement and its ripple effects, they only hire their own.

These are high paying jobs. Don’t see why it’s a problem!

i am sure balle balle will fix all your problems !! good luck !!

@aa

actually 16 directors, based on shared pastebin link, @a4 and @a5

179:Director, Software Engineering  Boxborough, MA  $280,900    $434,900 
180:Director, Software Engineering  San Jose, CA    $274,497    $463,500 
181:Director, Software Engineering  San Jose, CA    $274,497    $410,500 
182:Director, Software Engineering  Atlanta, GA $262,800    $385,700 
183:Director, Software Engineering  Austin, TX  $262,800    $385,700 
258:Director, Product Management    San Jose, CA    $230,100    $374,100 
259:Director, Product Management    San Jose, CA    $230,100    $374,100 
260:Director, Product Management    San Jose, CA    $230,100    $374,100 
290:Director, Engineering   Research Triangle Park, NC  $247,900    $363,700 
350:Product Marketing Director  New York, NY    $241,925    $333,300 
356:Director, Business Operations   Richardson, TX  $174,900    $276,300 
558:Director, Strategy & Planning   San Jose, CA    $296,622    $418,900 
559:Director, Strategy & Planning   San Francisco, CA   $244,200    $375,900 
560:Director, Strategy & Planning   Austin, TX  $200,400    $296,900 
591:Director, Business Product Manager  San Jose, CA    $280,100    $442,600 
618:Director, Technical Systems Engineering Research Triangle Park, NC  $187,800    $280,200 

Send them all home along with the 50 million illegals su-king our country dry.
Outlaw the offshoring as well.

@aa yup thats where your potato somosas come from ..

Director, Software Engineering 5

wow.. 5 directors being imported and will get their green cards quickly??

@a8 yes, that's how i saw it on that site. the data is for 2026 and wages are rising. for us who spent long time here this may look surprising.

Are these positions all H1B positions? If so, they seem higher than expected.

in that source data link, change "example" in example.com to pastebin

Full Source Data Set:

https://example.com/BpiiiSZV

I parsed the full Cisco Systems, Inc. dataset as 657 job-location wage-range records.

For the analysis, each row is treated as one observation. When both wage endpoints are available, the midpoint is calculated as:

(Wage From + Wage To) / 2

1. Dataset profile

The dataset is heavily concentrated geographically.

California accounts for 286 of 657 records, or about 43.5% of the dataset.

San Jose alone accounts for 158 records, or about 24.0%.

The top eight locations account for approximately 71.2% of all observations.

This matters because a simple companywide average is influenced heavily by Cisco's California and Bay Area positions.

2. Overall wage statistics

The midpoint distribution is moderately weighted toward higher salaries.

The average midpoint is about $197K, while the median is about $191K. A smaller number of highly compensated senior, director, AI, architecture and revenue-related positions pull the average upward.

Approximately:

• 45% of complete records have a midpoint of at least $200K.
• 12% have a midpoint of at least $250K.
• About 4% have a midpoint above $300K.

The published salary ranges themselves are also quite wide.

The median difference between Wage From and Wage To is approximately $88,600.

That range width is about 46% of the median midpoint.

Nearly 30% of the complete records have a published range at least $100K wide.

Because of this, the midpoint should not be interpreted as an expected salary offer. It is more useful as a standardized way of comparing ranges.

3. Standardized compensation bands

One of the strongest patterns in the dataset is that the salaries do not behave like hundreds of independently calculated ranges.

The same exact salary ranges appear repeatedly across different job titles and locations.

The most common exact ranges are:

The top 10 exact From-To combinations account for about 22.8% of the entire dataset.

The top 50 combinations account for about 51.1%.

This strongly suggests that Cisco uses reusable compensation bands across different roles, levels and geographic markets.

A simplified way of thinking about the structure would be:

Job family / level + geography + possible role-specific adjustment = compensation band

rather than every individual job title having a completely independent salary range.

4. Job title is the dominant compensation variable

I tested how much of the variation in salary-range midpoint can be statistically associated with job title and location.

A model using job title alone explains approximately:

73.9% of midpoint variation

A model using location alone explains approximately:

32.8% of midpoint variation

A model using both exact job title and location explains approximately:

87.6% of observed midpoint variation

This suggests that Cisco compensation in this dataset is highly structured.

Job title and role level appear to be the primary drivers of compensation, while geography adds another significant layer.

The 87.6% figure should not be interpreted as a predictive accuracy score. There are many job titles and locations relative to the number of records, so some of the statistical fit reflects the large number of categories.

The more useful conclusion is the relative one:

Job title matters considerably more than geography, but geography still has a substantial effect.

5. Major role comparisons

For exact job titles with enough observations to make comparisons more meaningful:

A visible progression appears within the software engineering career path.

Software Engineer has a median midpoint of approximately:

$183,750

Software Engineering Technical Leader rises to approximately:

$243,450

Leader, Software Engineering is very similar at approximately:

$244,270

Director, Software Engineering rises to approximately:

$342,498

That is roughly 86% above the Software Engineer median midpoint.

The data suggests that Cisco's senior technical and engineering leadership tracks can reach compensation levels comparable to traditional management positions.

1. AI and data roles

There is a noticeable hierarchy inside the data and AI family.

AI Researcher has the strongest median midpoint among these exact titles.

Data Scientist, Data Engineer and Machine Learning Engineer are surprisingly close, with median midpoints around $200K-$202K.

Data Analyst is in an entirely different compensation tier at about $117K.

This suggests that Cisco's "data" terminology covers very different job levels and occupational classes. Combining Data Analyst, Data Scientist, Data Engineer and AI Researcher into a single "data jobs" category would produce misleading results.

1. Geographic compensation structure

Raw median midpoint by major location:

Raw location comparisons can be distorted because each location has a different mix of jobs.

To reduce that effect, I also compared compensation within the same exact job title. The approximate title-adjusted geographic differences were:

Even after approximately controlling for exact job title, Bay Area compensation remains noticeably higher.

Austin, Research Triangle Park, Richardson and Morrisville generally fall below the corresponding title average.

This should not be interpreted as a precise geographic pay premium because the data does not contain explicit job level, experience, organization, specialization or requisition information.

1. Software Engineer provides a useful controlled example

Software Engineer has 93 observations, making it the strongest single title in the dataset for comparing locations.

The average San Jose Software Engineer midpoint is roughly 26% above Austin.

Milpitas is roughly 29% above Austin.

This supports the broader finding that the geographic differences are not simply caused by California having more senior job titles.

1. Range width contains information of its own

Wage From and Wage To are highly correlated, as expected:

corr(Wage From, Wage To) = 0.851

Range width also increases substantially with compensation level:

corr(Midpoint, Range Width) = 0.704

In other words, higher-paid and more senior jobs generally have wider salary ranges.

Some of the widest ranges are concentrated in Account Executive and Solutions Engineer positions.

Examples:

Account Executive - Architecture - San Jose
$168,958 - $480,300
Range width: $311,342

Account Executive - Architecture - Nashville
$147,077 - $432,400
Range width: $285,323

Account Executive - Services & Software Buying Programs - Santa Monica
$119,475 - $404,100
Range width: $284,625

These positions behave very differently from standard technical salary bands and probably should be analyzed separately from engineering roles.

This is also why Wage To alone can be misleading when comparing positions. The midpoint is generally more useful statistically, but the width of the range should also be considered.

1. Extreme observations

The highest lower bound in the data is:

Director, Strategy & Planning - San Jose
$296,622 - $418,900

The highest upper bound is:

Account Executive - Architecture - San Jose
$168,958 - $480,300

The highest midpoint is:

Director, Software Engineering - San Jose
$274,497 - $463,500
Midpoint: $368,999

The lowest midpoint is:

Network Support Engineer - Savannah, GA
$78,915 - $114,500
Midpoint: $96,708

The overall spread from the lowest midpoint to highest midpoint is approximately 3.8x.

1. Data-quality issues

There are several cleaning issues worth noting before drawing conclusions from the data:

• "MORRISVILLE, NC" occurs with different capitalization than "Morrisville, NC".
• "Charlotte,, NC" contains a double comma.
• Some job titles contain inconsistent multiple spaces.
• "Bromfield, CO" should be validated as a location.
• One record has no upper wage value.
• There are 68 additional repeated title/location/range records.

Those repeated records should not automatically be treated as duplicates. They could represent separate job postings using the same compensation band. Without a requisition or case identifier, there is no way to distinguish duplicate ingestion from legitimate repeated positions.

1. What I think the dataset is really showing

The strongest structural interpretation is:

Cisco compensation in this dataset appears organized primarily around job/level bands, modified substantially by geography.

The evidence for this is fairly strong because more than half of all observations can be represented by just 50 exact salary-range combinations.

The hierarchy appears roughly:

Support / analyst < standard engineer / specialist < senior technical / architecture < technical leader / leader < director / distinguished

Geography then shifts those bands upward or downward.

AI Researcher stands out among specialized individual contributor roles, while technical-leader positions show that Cisco's senior technical career track can reach compensation territory normally associated with management.

The Bay Area shows a persistent premium even after controlling for exact job title. Austin, Research Triangle Park, Morrisville, Richardson and Atlanta generally sit below the corresponding title average.

The dataset also shows that Wage To should not be used by itself to rank jobs. This is especially important for Account Executive and Solutions Engineer positions, where the upper endpoint can be extremely far from the lower endpoint.

Midpoint is statistically more useful for comparison, but even midpoint should be considered together with the width of the salary range.

Bottom line

For analytical purposes, I would model this dataset using:

Job Title/Family + inferred Level + Geography + Range Midpoint + Range Width

rather than simply ranking Cisco jobs by Wage From or Wage To.

The most important quantitative results are:

• Median salary-range midpoint: about $190.7K
• Median range width: about $88.6K
• Job title alone explains roughly 74% of midpoint variation
• Job title plus location explains roughly 88% of observed midpoint variation
• Bay Area locations show a clear compensation premium
• More than half of the records fall into just 50 exact salary-range combinations
• Senior technical roles can reach compensation levels comparable to management
• The data strongly suggests reusable corporate compensation bands rather than independently determined salary ranges for every posting