Project Coordinator

Substitutions:

• J.D. or master’s degree and six years of specialized experience.
• Ph.D. and five years of specialized experience

PREFERRED QUALIFICATION: Ability to initiate and maintain relationships across a diverse set of stakeholders

• Lead a cross-agency comprehensive effort to monitor and measure data from educational institutions, employers, and workforce development programs.
• Responsible for integrating data into a longitudinal data tracking system to assess the long and short-term outcomes of workforce development interventions.
• Support enterprise data governance.
• Demonstrate the ability to extract and process data from structured and unstructured data sets.
• Responsible for managing and training staff in the Bureau in areas of subject matter expertise.
• Collaborate with economists, analysts, and others working in this area to identify relevant public and confidential data sources (labor market data, education data, etc.).
• Develop data pipelines to extract data from various sources, ensuring secure access to confidential data.
• Collaborate with economists, analysts and others working in this area to identify relevant public and confidential data sources (labor market data, education data, etc.)
• Develop data pipelines to extract data from various sources, ensuring secure access to confidential data.
• Clean and pre-process the data to handle inconsistencies, missing values, formatting issues, etc. Design and implement a secure data storage system to handle large volumes of data from diverse sources.
• Support the development and maintenance of data warehouses and lakes for efficient data retrieval and analysis. Ensure data security and access control, especially for confidential data. Work with economists, analyst, and others to define research questions and identify relevant data points.
• Develop statistical models and machine learning algorithms to analyze essential trends, relationships, and patterns in the data.
• Conduct exploratory data analysis (EDA) to understand the data’s characteristics and potential biases.
• Collaborate with economists, analysts, and others working in this area to create non-technical informative dashboards, reports, and visualizations for public consumption.
• Design benchmark and metrics relevant to the economic research being conducted. Explore and implement AI techniques, such as natural language processing (NLP, to analyze textual data within the system.
• Develop machine learning models for forecasting, anomaly detection, or data segmentation on approved datasets. Ensure responsible AI practices by mitigating bias and ensuring model explainability.