Unlocking the Global AI Talent Landscape
Project Description
Are you interested in using data intelligence to uncover insights about the global AI talent ecosystem?
We are launching a research project using a large-scale professional profile dataset (similar to LinkedIn), covering individuals’ job history, skills, roles, and career trajectories across regions. The project aims to analyze patterns in AI and tech talent distribution, growth areas, and policy-relevant insights for talent development—focusing on Hong Kong, Greater China, and international benchmarks.
We are launching a research project using a large-scale professional profile dataset (similar to LinkedIn), covering individuals’ job history, skills, roles, and career trajectories across regions. The project aims to analyze patterns in AI and tech talent distribution, growth areas, and policy-relevant insights for talent development—focusing on Hong Kong, Greater China, and international benchmarks.
Supervisor
YANG Yi
Quota
1
Course type
UROP1100
Applicant's Roles
What You’ll Do:
- Analyze real-world workforce data at scale
- Extract trends in AI-related skills, job transitions, and regional talent hubs
- Generate insights to inform talent policy and education strategies
Who We’re Looking For:
- Undergraduate students in Computer Science or related fields
- Familiar with big data tools (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Snowflake, StarRocks)
- Curious, self-driven, and excited about applying data science to real-world impact
- Analyze real-world workforce data at scale
- Extract trends in AI-related skills, job transitions, and regional talent hubs
- Generate insights to inform talent policy and education strategies
Who We’re Looking For:
- Undergraduate students in Computer Science or related fields
- Familiar with big data tools (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Snowflake, StarRocks)
- Curious, self-driven, and excited about applying data science to real-world impact
Applicant's Learning Objectives
- Gain hands-on experience in large-scale data processing using tools such as Spark, Hadoop, and cloud platforms like AWS or Snowflake.
- Develop practical skills in data cleaning, feature engineering, and scalable analytics on semi-structured and unstructured profile data.
- Learn how to extract actionable insights from real-world workforce data and understand AI talent dynamics across regions.
- Apply data science methods to address policy-relevant questions in education, labor markets, and technological innovation.
- Develop practical skills in data cleaning, feature engineering, and scalable analytics on semi-structured and unstructured profile data.
- Learn how to extract actionable insights from real-world workforce data and understand AI talent dynamics across regions.
- Apply data science methods to address policy-relevant questions in education, labor markets, and technological innovation.
Complexity of the project
Challenging