AI Job Market Analysis Project Using Tableau (Part-1)
- Gunashree Ramachandran
- Jan 12
- 6 min read
In this blog I like to Present my one more Tableau project. I analyzed AI JOB MARKET DATASET using Tableau. As we know How AI changing the Existing job market by Seeing social media, by hearing so many stories from friends, colleagues and Gossips from surroundings .AI job market is changing so fast that its almost feels like every week there’s a role, new skill or a new salary trend is popping up.
With so much happening, I wanted to take a step back and see what the data says. So, I downloaded a dataset of AI job market from KAGGLE.com and explored it in Tableau to understand where the opportunities are growing, which skills matter most, and how the landscape is shifting. This quick visual look gives what’s really going on around the world of AI careers.
In this project let’s see how organization across industries -technology, healthcare, finance, retail, and manufacturing are driving in the race of AI. I built an interactive Tableau dashboard that analyzes AI job postings, skills demand, salary trends, Experience, Work mode and geographic.
This blog walks through the insights uncovered and how Tableau helps transform raw job data into actionable workforce intelligence.
What is Artificial Intelligence -AI?
Artificial Intelligence, or AI, is basically the idea of teaching computers to think a little more like us. It learns from patterns, adapts to new information, and helps automate tasks we used to do manually. AI isn’t just for technical experts anymore; it’s into daily life, making things faster, smarter, and a bit more convenient. As the tech keeps evolving, it’s opening doors to new possibilities we’re only beginning to explore and analyze.
Why do we need to analyze the AI Job market?
AI adoption is no longer experimental. Companies are integrating machine learning, automation, and data‑driven decision systems into core operations.
A spike in demand for AI‑related roles
Rapid evolution of required skills
Salary inflation for specialized positions
Geographic clustering of AI opportunities
Industry‑specific hiring patterns
Understanding these trends helps job seekers, hiring managers, educators, and policymakers make informed decisions.
Data Set Overview
I downloaded
the Data set from Kaggle.com attached data below
Our data set includes
· Salary
· Job ID
· Industry
· Required skills
· Location
· Remote Category
· Benefit Ratio
· Education Required
· Experience Level
Also we have More Fields in Data set .
Tableau Level to Level Analysis
I connected my dataset to tableau Desktop
I created a relationship between data set like below
Job Count
This shows a direct count of unique job entries, calculated using CNT (Job Id)
Salary vs Job Count Analysis
In this Scatter Plot in tableau, I compared the average salary against the Job postings by country.
Each plot represents the country, and the color shows the industry level.
From this analysis U.S. leads in both salary and job volume, But India and China have tons of jobs, but the average salary is much lower. Countries like Switzerland, Norway, and Singapore offer high pay, but fewer.
AI Adoption by Industrial Level
Next, lets analyze which industry is using Ai Adoption. But when you dig into the data, the story gets a lot more interesting. I built a Tableau chart that breaks down AI adoption across industries and groups them into three buckets: High, Medium, and Low adoption.
Technology and Finance are leading with tons of AI-related job activity. They’ve got the budget and the data .
Health and Manufacturing are catching up, sitting in the medium adoption zone. These industries are starting to use AI for diagnostics, automation, and predictive maintenance.
Education, Energy, and Entertainment are still warming up, showing lower levels of AI job activity. But that could change fast as tools get easier to use.
Each vertical bar in the chart shows how many AI-related job insights came from each industry. It’s a simple way to see who’s investing in AI.
This type of Analysis breakdown helps job seekers, analysts, and even educators understand where the AI wave is hitting hardest.
Average Salary by Country
Each row lists a country and its average salary in USD for AI jobs.
Switzerland, Denmark, and the U.S. offer the highest pay.
India, China, and South Korea have lower average salaries but may offer more entry-level opportunities.
The color coding helps quickly spot which countries pay more (green) and which pay less (red).
This table is useful for comparing global earning potential in the AI field.
Average Salary by Work Mode
I created a simple pie chart in Tableau comparing average salaries across three work mode Remote, Hybrid, and Onsite. After the COVID, every life changed with mode of work , after those Remote jobs came out slightly ahead, averaging around $116,161. Hybrid roles followed closely at $115,777, and Onsite jobs averaged $114,140. While the differences aren’t dramatic, they do suggest that companies are willing to pay a bit more for remote flexibility possibly to attract top talent or offset the lack of in-person perks.
This Breakdown helpful for job seekers weighing their options, and for employers thinking about how compensation aligns with work style. It’s a quick snapshot of how the AI job market values flexibility.
Average salary based on education level
Having a higher degree always means a higher paycheck in AI? I wanted to find out, so I built a simple bar chart in Tableau that compares average salaries across different education levels Associate, Bachelor, Master, and PhD.
The results were interesting. Master’s degree holders topped the chart with an average salary of $117,172, followed closely by bachelor’s at $115,862. Associate degrees weren’t far behind at $114,606. Surprisingly, PhD holders came in lowest at $113,728.
This chart shows how education level correlates with earning potential, but it also shows that the gap isn’t as wide as you might expect.
Average Salary by experience level
I built a bar chart in Tableau that breaks down average salaries by experience level Entry, Midlevel, Senior, and Executive and the results are clear.
Entry-level roles average around $63,133, which is solid for getting started. Midlevel jumps to $87,955, showing how quickly things scale once you’ve got a few years under your belt. Senior professionals earn about $122,188, and Executives top the chart at a whopping $187,724.
This chart gives what kind of salary range you might expect at each stage.
Remote Work by Country
World map in Tableau shows the percentage of AI jobs that offer remote work across different countries. China leads the pack with nearly 95% of AI roles offering remote options. India, Australia, and the U.S. also show strong support for remote work, with percentages ranging from 68% to 79%. On the flip side, European countries like Finland, Sweden, and Norway have much lower remote adoption. Visualization helps highlight global differences in work culture and flexibility.
Top 10 Countries by Job Count
When it comes to AI job opportunities, location matters and some countries are clearly leading the charge. I built a tree map in Tableau that shows the top 10 countries by job count, using data from AI-related postings. Each block represents a country, sized by the number of jobs and color-coded for easy comparison.
The results are evenly spread, with France, Denmark, and India showing slightly higher job volumes, each around 770–780 postings. Germany, China, and Canada follow close behind, while Finland and Australia round out the list.
This chart is useful for job seekers exploring global options or analysts tracking regional growth.
Top 10 common AI Skills
This bubble chart in Tableau visualizes the top 10 most common AI-related skills found across job postings. Each bubble represents a skill, and the size shows how frequently it appears.
Who pays Most and Least Salary for AI Roles
I built the Heat Map to compare average salary and benefits scores across a range of AI job titles and companies.
Each cell shows how well a specific company pays for a specific role. The greener the box, the better the compensation and perks. The red color is less generous things look. Roles-like Head of AI, Principal Data Scientist, and AI Architect tend to score high, especially at companies like Quantum Computing Inc and Tech Corp Inc. Some companies offer lower packages for roles like AI Specialist or Data Analyst, depending on their size and focus.
Final Analysis of project.
The dataset shows an AI job market growing fast but unevenly, with top salaries concentrated in engineering‑heavy roles like ML engineering, data engineering, and AI infrastructure. Mid‑tier roles applied data science, AI product analysis, and prompt‑focused position reflect a shift toward operationalizing and governing AI rather than just building models. Skill patterns emphasize Python, cloud platforms, and MLOps, signaling a market focused on scalable deployment. Overall, the market where engineering depth drives compensation, while the fastest expansion is happening in roles that translate AI into reliable, business‑aligned systems.
Attached My AI JOB ANALYSIS Project In Tableau https://public.tableau.com/app/profile/gunashree.ramachandran/viz/JOBANALYSIS_FINALdASHBOARD/Dashboard1?publish=yes
DASH BOARD
In my upcoming Blog, I take you how to Build and design Home Page using my AI Job Analysis in more Stylish way Let’s explore in future blogs.
Thank You
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