LinkedIn's 2023-24 US Math Teacher Jobs 📐🚀

Overview

This dataset, titled "LinkedIn's 2023-24 US Math Teacher Jobs 📐🚀", presents a curated collection of math teacher job listings across the United States, as sourced from LinkedIn during the latter part of 2023 up to February 2024. It offers a unique snapshot of the educational job market, specifically focusing on opportunities in math education. This compilation serves not only as a resource for job seekers but also as a rich dataset for data scientists interested in labor market trends, educational job dynamics, and the burgeoning demand for math educators in the digital age.

Data Science Applications

As a moderate-sized dataset, it strikes a balance between comprehensiveness and manageability, making it ideal for a wide range of data science projects. Its raw form, complete with missing values and unprocessed columns, provides an excellent opportunity for data cleaning practice, honing skills that are pivotal in the initial stages of data analysis. Beyond cleaning, the dataset is ripe for exploratory data analysis (EDA), trend identification, geographic distribution mapping, and temporal analysis of job posting frequencies. Furthermore, it offers a practical basis for more advanced applications such as predictive modeling of future job market trends, natural language processing (NLP) for job description analysis, and network analysis to explore connections between different sectors and job titles.

Column Descriptors

The dataset contains the following columns, each offering a different facet of the job listing:

• Title: The job title.
• Location: Geographic location of the job.
• PostedTime: How long ago the job was posted.
• PublishedAt: The date the job listing was published on LinkedIn.
• JobUrl: URL to the full job listing on LinkedIn.
• CompanyName: The name of the hiring organization.
• Description: A brief overview of the job role and responsibilities.
• ApplicationsCount: The number of applicants or a related metric.
• ContractType: The nature of the employment contract (e.g., Full-time, Part-time).
• ExperienceLevel: Required experience level for the position.
• WorkType: The category of work.
• Sector: The sector of employment.
• Salary: The offered salary (note: this column contains a significant number of missing values).

Ethically Mined Public Data

This dataset has been ethically mined, strictly adhering to public data access guidelines and privacy standards. It comprises information that was publicly available on LinkedIn, ensuring that no private or sensitive data has been compromised in its compilation.

Acknowledgements

We extend our gratitude to LinkedIn for hosting such valuable data, enabling insights into the educational job market and contributing to the broader understanding of employment trends in the field of math education.

Additionally, we acknowledge the use of DALL·E 3 for generating the captivating image that serves as this dataset's thumbnail. This image, designed to echo the dataset's theme and content, has been created specifically to represent the opportunities and growth in the math education sector as depicted through the dataset.