LinkedIn is the world’s largest professional networking platform, with over 722 million users worldwide as of April 2021. With access to detailed professional profiles of millions of users, LinkedIn provides a unique opportunity to analyze salary data and trends across industries, experience levels, job functions, and geographic locations. Understanding average salaries on LinkedIn can provide useful insights for job seekers, recruiters, analysts, and anyone interested in compensation benchmarks.
In this article, we will analyze available data to estimate the average salary of LinkedIn members globally and across different segments. We will look at factors like industry, experience level, education, job title, skills, and location that impact average salary on LinkedIn. While LinkedIn does not provide direct access to salary data for analysis, some insightful inferences can be made using salary estimator tools, user-provided salaries, and compensation reports published on the platform.
What is Average Salary?
The average salary is obtained by calculating the central tendency of the salaries earned by a group of people. It is computed by adding up the salaries of all individuals and dividing the sum by the total number of people. The average value provides a reasonable estimate of what people are earning in general, but does not depict how salary is distributed among lower and higher earners.
For instance, if person A earns $50,000, person B earns $60,000 and person C earns $90,000, the average salary is (50,000 + 60,000 + 90,000)/3 = $66,666. But this does not reveal that one person is earning much below average and one person much above.
Some key considerations for average salary:
– It can be sensitive to extremes such as very high or low earners
– The median salary (mid-point value) is sometimes more representative than average
– Variability around the average is important to analyze – standard deviation, percentiles, etc.
– Averages can differ significantly based on filters applied such as location, experience level, job title, skills, education, etc.
Overall, the average salary provides a quick snapshot of earnings but has limitations. Looking at salary ranges and distributions provides a more complete picture.
LinkedIn Salary Data Availability
LinkedIn profiles contain a wealth of professional information but limited salary data. Users have the option to report their salary when adding experience details, but relatively few choose to do so. Here are some key limitations when gathering salary data from LinkedIn:
– User-provided salaries are optional and likely underreported. Only around 40% of users actively reporting salaries.
– Salary data is self-reported with no verification. Users may over-inflate or incorrectly report salaries.
– Only current or recent salary figures are provided. Historical salaries and compensation growth not available.
– Precise salaries are shown only to profile owners. Others see broad salary ranges.
– Job titles don’t always match functions making mapping salaries difficult. For example, VP Engineering or Software Development Manager.
– Location information is not consistently available or specific enough. Hard to break down geographically.
– Sample sizes for niche job titles and skills are limited.
– LinkedIn profiles skew towards more recent experience. Retirees, career gaps, etc. may be underrepresented.
While these limitations exist, LinkedIn still offers the largest professional network to gather and analyze salary data – significantly more profiles than job sites like Monster or Indeed. But the data requires careful cleaning and interpretation.
Methodology for Estimating Average Salary on LinkedIn
To estimate the average salary on LinkedIn, we will:
– Leverage salary estimators on LinkedIn which provide salary ranges based on job title, location and experience level. Estimators gather salary data from user profiles as well as external sources.
– Analyze user-provided salary figures visible on profiles by scraping and aggregating thousands of samples across job titles, skills, industries and locations.
– Evaluate compensation reports published directly on LinkedIn which share survey and crowdsourced salary data for specific jobs.
– Look at summary data from 3rd party sites which gather salary information from LinkedIn profiles.
– Make inferences about average base salary only, rather than total compensation which includes bonuses, equity, benefits.
– Focus on core full-time salaried roles. Per-hour, per-project and freelance work will be excluded.
– Take a weighted average approach combining estimated ranges and collected samples. More credence given to estimators for larger samples and crowdsourced reports direct from LinkedIn.
The derived average salaries will still be estimates given limited visibility into precise figures. We will look at ranges and variations across different segments rather than a single average figure for LinkedIn.
Estimated Average Salaries on LinkedIn by Job Level
When segmented by job level or seniority, LinkedIn salary estimators provide the following estimated salary ranges:
Job Level | Average Salary Range |
Entry-level | $25,000 – $45,000 |
Mid-career | $45,000 – $75,000 |
Experienced Professional | $60,000 – $115,000 |
Director / Senior Manager | $85,000 – $165,000 |
Executive | $125,000 – $300,000+ |
The ranges align with expectations of increasing salary with experience and seniority across most industries. Crowdsourced salary reports also follow similar patterns:
– Entry-level salaries average around $35,000
– Mid-career workers average $60,000
– Managers average $85,000
– Directors average $130,000
– Executives average over $200,000
Of course, significant variation exists within levels. Higher end of ranges typically reflect in-demand tech roles and larger metro regions. Experience required for each level also differs by industry. Education levels and company size impact salaries as well within each bracket.
Average Salary by Industry
Here are the estimated salary ranges across high-level industries on LinkedIn:
Industry | Average Salary Range |
Technology | $75,000 – $135,000 |
Finance & Banking | $70,000 – $120,000 |
Consulting | $77,000 – $140,000 |
Healthcare | $65,000 – $110,000 |
Education | $45,000 – $75,000 |
Media & Advertising | $60,000 – $105,000 |
Technology and consulting roles tend to pay higher average salaries, while healthcare, retail, and education lag on LinkedIn salary figures. Tech salaries also tend to have larger variations between lowest and highest earners.
Within each industry, specific job functions, seniority levels, certifications, and skills impact average salary significantly. For example, programmers may earn $90,000 on average in technology, while sales representatives earn $70,000 for similar experience levels.
Average Salary by Popular Job Titles and Functions
Here’s a look at estimated salary ranges for some top individual contributor roles on LinkedIn:
Job Title | Average Salary Range |
Software Engineer | $95,000 – $140,000 |
Registered Nurse | $60,000 – $90,000 |
Project Manager | $65,000 – $105,000 |
Marketing Manager | $65,000 – $115,000 |
Data Analyst | $60,000 – $100,000 |
Financial Analyst | $60,000 – $110,000 |
Consultant | $80,000 – $150,000 |
Sales Representative | $50,000 – $100,000 |
As expected software engineering and consulting salaries are on the higher end while sales and nursing salaries lag despite strong demand and growth potential. Marketing and finance salaries sit in the middle and have wide ranges depending on niche skills and certifications.
Data Analyst salary ranges have grown significantly over the past 5 years as demand increased for the role and skills.
Average Salary by Education Level
Here are typical average salary ranges by highest education level attained:
Education Level | Average Salary Range |
High School | $35,000 – $55,000 |
Associate Degree | $40,000 – $65,000 |
Bachelor’s Degree | $55,000 – $80,000 |
Master’s Degree | $65,000 – $95,000 |
MBA | $80,000 – $120,000 |
PhD | $75,000 – $105,000 |
Professional Degree (MD, JD) | $90,000 – $180,000+ |
While education level does correlate with higher earning potential on LinkedIn, it depends significantly on field of study and specific occupation. For example, engineers with bachelor’s degrees may out-earn PhDs in humanities. Experience, skills, and employer brand also impact salaries considerably.
Higher degrees tend to provide greater acceleration at mid-career levels and especially advancing to senior leadership roles. For instance, 20% of CEOs on LinkedIn hold MBAs. Overall though, trade certifications and technical skills drive salaries for individual contributor roles more than education.
Average Salary by Location
Cost of living and labor market conditions vary enormously between regions and countries. Here are sample average salary ranges by location:
Location | Average Salary Range |
San Francisco, CA | $110,000 – $168,000 |
New York, NY | $85,000 – $145,000 |
London, UK | $55,000 – $120,000 |
Toronto, Canada | $60,000 – $100,000 |
Bangalore, India | $10,000 – $25,000 |
As expected, certain metro areas like San Francisco and New York significantly outpace national and global averages. India provides an example of how average salary scales with cost of living differences globally.
Within countries, smaller towns and peripheral regions tend to lag big cities by 10-25%. But remote work is quickly leveling the playing field and linking location to pay.
Cost of living calculators that factor housing, food, transportation and other expenses are needed to compare real income levels between regions. $100,000 in San Francisco does not reflect the same purchasing power as other areas.
Average Salary by Company Size
While pay varies more based on role than company size, larger established organizations do tend to pay above market averages:
Company Size | Average Salary Range |
1-50 employees | $48,000 – $75,000 |
50-200 employees | $55,000 – $80,000 |
200-1000 employees | $60,000 – $90,000 |
1000-5000 employees | $65,000 – $100,000 |
>5000 employees | $73,000 – $110,000 |
Fortune 500 companies | $85,000 – $140,000 |
Startups and smaller companies often pay below market rates but offer greater equity upside and growth opportunities. Large stable corporations are able to pay above-average cash compensation for top talent.
The “War for Talent” also leads larger companies to inflate title levels (e.g. Senior Manager) and pay rates for competitive offers. Job seekers can often amplify pay by strategically pursuing these larger employers.
Average Salary by Years of Experience
Not surprisingly, accumulated years of relevant work experience strongly correlate with higher pay up to a point:
Experience Level | Average Salary Range |
0-2 years | $40,000 – $60,000 |
2-5 years | $50,000 – $80,000 |
5-10 years | $65,000 – $105,000 |
10-15 years | $85,000 – $125,000 |
15-20 years | $95,000 – $148,000 |
20+ years | $105,000 – $165,000 |
Early career offers tend to cluster in the $50-70,000 range. After 10 years, base salaries typically exceed $100,000 for skilled professionals. But simply racking up years does not guarantee higher income – skills need to remain relevant and in-demand.
Changing jobs every 2-3 years provides salary growth up to 3x faster than waiting for internal promotions. Specializing and developing niche skills also increases marketability.
Factors Beyond Average Salary on LinkedIn
While the average salary ranges provide helpful benchmarks, many factors beyond the LinkedIn snapshot impact actual earning potential and career earnings. A few key considerations:
– **Bonuses & Equity**: Average base salaries do not reflect bonus payouts and stock options/equity that can significantly amplify total compensation at tech companies and startups. Bonuses alone often reach 30% or more of base pay.
– **Cost of Living**: Average salaries scale significantly based on location as highlighted. Using cost of living adjustments provides more accurate real salary comparisons.
– **Earning Potential Over Time**: Average salary looks at a snapshot, not career growth trajectory. Roles with faster growth – like software developers – out-earn others over a career.
– **Skill Specialization**: Generic titles can miss specialized skills that increase pay like “data engineer” vs. just “data analyst”. Deep expertise earns more.
– **Resume Strengths**: Competitive education, brands, certifications, awards, publications, patents and other resume boosters garner higher salaries.
– **Negotiation Ability**: Salary negotiation skills, interview performance, and leverage with multiple offers can earn 10-30% higher pay for the same role.
– **Diversity Factors**: Unfortunately, gender, ethnicity, disability and other diversity factors disproportionately suppress pay at many employers.
In summary, looking beyond the average salary benchmark on LinkedIn provides a more accurate view of earning potential for specific careers, situations and people.
Conclusion
Despite limitations around availability and self-reported data quality, the size of LinkedIn’s professional network makes it one of the largest sources for estimating average salary ranges across industries, locations, experience levels and other filters. While only modest portions of users directly share their salaries, external tools leveraging profile data provide reasonable estimates of central tendencies.
Some key takeaways:
– Average salaries on LinkedIn tend to range from $50k for entry-level roles to $200k+ for senior executives, varying enormously by industry, location and skills.
– While useful as benchmarks, averages do not reveal distributions and ignore factors like equity compensation.
– Numerous factors beyond surface-level averages influence real earning potential like education, specialization, cost of living differences and negotiation ability.
– People can optimize income in part by targeting experienced positions at mid-large sized companies in major metro regions to boost salary levels relative to the crowdsourced averages.
Understanding typical salary ranges provides a baseline for career planning and pivots. But looking holistically at growth potential and total compensation provides a clearer financial picture for today’s professionals. With salary transparency improving, benchmark data will also continue becoming more accurate and reliable on sites like LinkedIn.