Job Description

Major Responsibilities:

• Use SQL, Python, or other analytical tools to query, clean, and analyze large datasets.
• Analyze labor market trends across dimensions such as workforce composition, job demand, employment patterns, and wage dynamics.
• Apply advanced techniques including time series forecasting, clustering, regression analysis, and machine learning algorithms (e.g., decision trees, random forests, gradient boosting, support vector machines, k-means clustering) to identify patterns and forecast labor trends.
• Build and maintain scalable data and model pipelines using orchestration tools like Apache Airflow, Luigi, or Sagemaker Pipelines, and model tracking tools such as MLflow.
• Collaborate cross-functionally to define problem statements, gather and analyze data, integrate models into products, and translate insights into actionable recommendations for technical and non-technical audiences.
• Stay informed on advancements in labor market analytics, statistical modeling, and machine learning technologies.

Education and Experience:

• Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field.
• 2+ years of industry experience or academic research applying statistical or machine learning approaches to real-world data problems.
• 2+ years of experience in labor market analytics, workforce intelligence, or related domains (preferred).
• Proficiency in Python, SQL, and machine learning libraries such as Scikit-learn or PyTorch.
• Demonstrated ability to write clean, scalable code and independently prototype data solutions.
• Solid understanding of machine learning techniques such as classification, regression, and time-series forecasting.
• Experience with cloud platforms (e.g., AWS) and orchestration tools like Apache Airflow for managing large datasets and workflows.
• Strong statistical reasoning and ability to translate complex data into strategic business insights.
• Excellent interpersonal, written, and verbal communication skills, with the ability to convey technical topics to diverse audiences.
• Experience working with large labor market datasets (e.g., government labor statistics, survey data, or job market intelligence platforms) (preferred).
• Proficiency with data visualization tools such as Tableau, Power BI, or Plotly (preferred).
• Familiarity with Natural Language Processing (NLP) techniques and applications (preferred).