Lightcast is looking to analyze labor market trends, workforce dynamics, and economic patterns to develop innovative models, datasets, and visualizations that provide actionable insights into the future of work.
Requirements
- 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.
- 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).
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.
Other
- 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.
- Excellent interpersonal, written, and verbal communication skills, with the ability to convey technical topics to diverse audiences.
- 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).
