Data_Skill_Radar

Project Overview

Analysis of LinkedIn job postings, focusing on data analytics and data scientist roles in the US and Spain (Barcelona and Madrid).

Table of Contents

1. Data Source
2. Objectives
3. Methodology
4. Tools and Technologies
5. Results and Findings
6. Conclusions
7. Links

1. Data Source

• Linkedin job posts

2. Objectives

• Identify the top skills required for data analytics and data scientist roles.
• Analyze trends in the demand for certain skills.
• Explore correlations between skills, industries, and job titles.

3. Methodology

Outline the methods used in the project, including:

• Web scraping (BeautifulSoup, Selenium).
• Data cleaning and preprocessing techniques.
• Natural Language Processing (NLP) for skill extraction.
• Clustering for skill grouping.
• Statistical analysis methods.
• Dashboard creation (Tableau).

4. Tools and Technologies

• Python (BeautifulSoup, Pandas, Nltk, Scikit-learn)
• Tableau for visualization
• Jupyter Notebook

5. File Descriptions

6. Results and Findings

Challenges and Learnings

7. Links

Canva Presentation: https://www.canva.com/design/DAF2MnWbo9w/rDOr5A3_XC5ir5Blp95N1w/view?utm_content=DAF2MnWbo9w&utm_campaign=designshare&utm_medium=link&utm_source=editor