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ad688-employability-sp25a1-group10

Project 1

https://github.com/hongan2908/ad688-employability-sp25a1-group10

Science Score: 44.0%

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Repository

Project 1

Basic Info
  • Host: GitHub
  • Owner: hongan2908
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 1.55 MB
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  • Watchers: 2
  • Forks: 0
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Created about 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Citation

README.md

Job Market Analysis 2024

This project was developed as part of the AD688 course at Boston University. Our team explored labor market trends in 2024 to help job seekers identify promising career paths using real-world data and analytics.

=e Team Members

  • An Ly
  • Advait Pillai
  • Ritusri Mohan
  • Shreya Mani

< Project Objective

To analyze salary and compensation trends across AI and non-AI careers using the Lightcast job postings dataset. We focused on understanding regional disparities, remote work patterns, industry-specific trends, and data-driven career planning.

= Key Deliverables

  • Data Cleaning: Removing missing values, redundant columns, and duplicates
  • EDA: Visualizations of job distribution by city, state, industry, and remote status
  • Predictive Insights: Trends related to AI career growth and salary divergence
  • Career Strategy: Individual action plans for each team member based on analysis

= Tools & Technologies

  • Python (pandas, seaborn, matplotlib, plotly)
  • Quarto & GitHub Pages
  • Lightcast Job Postings Dataset
  • VS Code, Jupyter Notebook

= Live Quarto Website

https://hongan2908.github.io/ad688-employability-sp25A1-group10/

= References

Citations and literature reviews are managed through references.bib and displayed on each .qmd file using Econometrica style.

Owner

  • Login: hongan2908
  • Kind: user

Citation (citation.qmd) 

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title: "References"
subtitle: "Salary & Compensation Trends - Job Market Analysis 2024"
author:
  - name: Group 10
    affiliations:
      - id: bu
        name: Boston University
        city: Boston
        state: MA
format: 
  html:
    toc: true
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## Predictive Salary Modelling: Leveraging Data Science Skills and Machine Learning for Accurate Forecasting
Haseeb, M. A., Viswanathan, R., Iyer, K., Hota, A. R., & Prathaban, B. P. (2024). Predictive salary modelling: Leveraging data science skills and machine learning for accurate forecasting. 2024 9th International Conference on Communication and Electronics Systems (ICCES), 1011–1019. https://ieeexplore.ieee.org/document/10859447

## Tackling Economic Inequalities Through Business Analytics: A Literature Review
Adaga, E. M., Egieya, Z. E., Ewuga, S. K., Abdul, A. A., & Abrahams, O. (2024). Tackling economic inequalities through business analytics: A literature review. Computer Science & IT Research Journal, 5(1), 60–80. https://doi.org/10.51594/csitjr.v5i1.702

## Antecedent Configurations Toward Supply Chain Resilience: The Joint Impact of Supply Chain Integration and Big Data Analytics Capability
Jiang, Y., Feng, T., & Huang, Y. (2024). Antecedent configurations toward supply chain resilience: The joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, 70(2), 257–284. https://doi.org/10.1002/joom.1282

## Leveraging AI and Data Analytics for Enhancing Financial Inclusion in Developing Economies
Adeoye, O. B., Addy, W. A., Ajayi-Nifise, A. O., Odeyemi, O., Okoye, C. C., & Ofodile, O. C. (n.d.). Leveraging AI and data analytics for enhancing financial inclusion in developing economies. Finance & Accounting Research Journal. https://fepbl.com/index.php/farj/article/view/856

## Employee Career Decision Making: The Influence of Salary and Benefits, Work Environment and Job Security
Achim, N., Badrolhisam, N. I., & Zulkipli, N. (2019). Employee career decision making: The influence of salary and benefits, work environment and job security. Journal of Academia, 7(Special Issue 1), 41–50.

## The Influence of Salaries and “Opportunity Costs” on Teachers’ Career Choices
Murnane, R. J., Singer, J. D., & Willett, J. B. (1989). The influences of salaries and “opportunity costs” on teachers' career choices: Evidence from North Carolina. Harvard Educational Review, 59(3), 325–349.

## The Future of Work: Impacts of AI on Employment and Job Market Dynamics
Tomar, A., Sharma, S., Arti, & Suman, S. (2024). The future of work: Impacts of AI on employment and job market dynamics. 2024 International Conference on Progressive Innovations in Intelligent Systems and Data Science (ICPIDS).

## AI and Job Market: Analysing the Potential Impact of AI on Employment, Skills, and Job Displacement
Faluyi, S. E. (2025). AI and job market: Analysing the potential impact of AI on employment, skills, and job displacement. African Journal of Marketing Management, 17(1), 1–8.

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