Data Analyst
Job Description
Responsibilities
• Requirements and Testing
- Work with program areas and project sponsor to gather business requirements and translate into technical specifications.
- Lead as Test Manager creating test plans and test cases that integrate from Agile sprint cycles, epics and stories, as well as Waterfall project plans and all project artifacts
- Translate complex data requests and operational requirements into clear, actionable queries for AI against complex analytics data sources.
- Explain technical findings and data limitations in simple, non-technical language to end-users.
• AI Prompting and Data Synthesis
- Develop and refine effective AI prompts and query strategies to retrieve and synthesize data accurately from complex datasets.
- Guide non-technical users in crafting precise prompts to get the data they need, ensuring fidelity and accuracy.
- Develop a library of standardized prompts and query templates for common reporting needs.
• Data Reporting and Visualization
- Extract, integrate, and analyze data from multiple complex internal and external sources to support HHS program needs.
- Collaborate with end-users and performance analysts or IT internal leaders to create and validate reports, dashboards, and data visualizations for program monitoring and official reporting.
- Provide subject matter expertise on validating output from AI, particularly with respect to identifying and mitigating hallucinations.
- Ensure all data outputs adhere to agency reporting standards, data governance, and compliance regulations.
• Data Literacy and Training
- Champion data literacy across the organization by developing and conducting AI training sessions for non-technical staff.
- Create clear, comprehensive documentation and tutorials on using AI tools for data synthesis.
- Promote a data-driven culture by enabling and empowering all employees to effectively utilize data and AI.
• Collaboration and Problem-Solving
- Work closely with data engineering, IT, and Program teams to troubleshoot data-related issues and address inconsistencies and mitigation strategies.
- Provide expert guidance to program staff on interpreting data trends and answering complex data questions.
- Stay up to date on new AI and data analytics tools and techniques to continuously improve data access, data quality and reporting.
CANDIDATE SKILLS AND QUALIFICATIONS
| Years | Required/Preferred | Experience |
| 10 | Required | Experience gathering business requirements and translating complex data requests and operational requirements into clear, actionable queries for complex analytics data sources |
| 10 | Required | Experience explaining technical findings and data limitations in simple, non-technical language to end-users. |
| 10 | Required | Experience in a complex data analysis, senior business/systems analyst, and/or data liaison role. |
| 10 | Required | Strong experience with SQL for data extraction and manipulation. |
| 10 | Required | Experience collaborating with end-users and performance analysts or IT internal leaders to create and validate reports, dashboards, and data visualizations for program monitoring and official reporting. |
| 10 | Required | Excellent communication, presentation, and interpersonal skills. |
| 10 | Required | Experience with data visualization tools such as Power BI and/or Tableau. |
| 5 | Preferred | Experience with Business Intelligence/Data Warehouse |
| 5 | Preferred | Experience working in a health and human services or similarly regulated environment, with a strong understanding of program data and reporting requirements. |
| 5 | Preferred | Experience with data governance and data quality principles |
| 2 | Preferred | Experience championing data literacy across the organization by developing and conducting training sessions for non-technical staff. |
| 2 | Preferred | Experience training and mentoring staff with varying levels of data literacy. |
| 1 | Preferred | Experience with creating AI prompt catalogs using tools such as Streamlit with Python. |
| 1 | Preferred | Experience applying responsible AI practices and compliance with agency standards. |
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