bazz-b / job-trend-analysis

Data analysis and modelling using ARIMA & SARIMA model

Job-Trend-Analysis

List of jobs posted using Linkedin & Jobstreet from 3 months.

Objective:

1. Support New Professionals: Provide entry-level workers with insights based on data to help them make decisions in today's job market.
2. Highlight In-Demand Skills: Identify the skills that are in high demand across various industries and clarify which ones professionals should pay attention to.
3. Understand Job Trends by Location: Look into the differences in job opportunities among various cities and states, providing important insights about different regions.
4. Forecasting Job Postings: Predict how job postings will change over time using ARIMA Models and SARIMA Models.

Summary of Analysis:

After analysis of the job postings dataset collected from LinkedIn and JobStreet, several key insights have emerged:

1. Explore Regional Employment Dynamics: Analyze variations in job opportunities across different cities and states to provide valuable regional insights
2. In-Demand Job Skills: Analytical skills, communication, and problem-solving are consistently sought across various job titles and industries. Technical skills such as Microsoft Excel, data analysis, and specific software expertise are prominently featured.
3. Explore Regional Employment Dynamics: Analyze variations in job opportunities across different cities and states to provide valuable regional insights. Main locations include Kuala Lumpur, Selangor, Penang and Johor as prominent cities with jobs.

Data Analysis

• Histogram:

Histogram bar of job postings that are distributed over the three months based on the dataset collected.

• Word Clouds:

To showcase the most frequently mentioned words in job skills. Gives us a glance into the job skills that are frequently highlighted in job postings.

• Bar Chart:

Illustrating the top five skills, categorized by different industries. Unlike the Word Cloud, this chart specifically breaks down the most crucial skills based on industry, providing a clearer understanding of the skill requirements in each sector.

• MAPS:

Use TABLEAU to generate maps and frequency of job postings based on location in Malaysia.

• ARIMA Model & SARIMA Model

To make predictions based on patterns from the data collected. A conclusion shall be made based on the value of Mean Absolute Error (MAE) and Mean Squared Error (MSE).

job-trend-analysis's Issues

Word Cloud

The most common job skills that appear on the database will be used.

Cannot distinguish what industry these job skills are used for.