Business Intelligence Analyst Specialist

Project Scope:

The Specialist position is rarely selected and should only be considered after all other levels have been exhausted. The Specialist position is considered an expert position that has a comprehensive and authoritative knowledge of or unique skillset in a particular area. The Business Intelligence Analyst use data to figure out market and business trends for companies to increase profits and efficiency. They may work directly for a company or as a consultant. They able to look at large chunks of data and understand trends, and then communicate those trends to the company.

Responsibilities:

As a senior analyst and tester on the agile development team, the worker responsibilities may include:

• • 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.

Mandatory Skills:

1. 10 Years- Experience gathering business requirements and translating complex data requests and operational requirements into clear, actionable queries for complex analytics data sources
2. 10 Years- Experience explaining technical findings and data limitations in simple, non-technical language to end-users.
3. 10 Years- Experience in a complex data analysis, senior business/systems analyst, and/or data liaison role.
4. 10 Years- Strong experience with SQL for data extraction and manipulation.
5. 10 Years- 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.
6. 10 Years- Excellent communication, presentation, and interpersonal skills.
7. 10 Years- Experience with data visualization tools such as Power BI and/or Tableau.

Desirable Skills:

1. 5 years- Experience with Business Intelligence/Data Warehouse
2. 5 years- Experience working in a health and human services or similarly regulated environment, with a strong understanding of program data and reporting requirements.
3. 5 years- Experience with data governance and data quality principles
4. 2 years- Experience championing data literacy across the organization by developing and conducting training sessions for non-technical staff.
5. 2 years- Experience training and mentoring staff with varying levels of data literacy.
6. 1 year- Experience with creating AI prompt catalogs using tools such as Streamlit with Python.
7. 1 year- Experience applying responsible AI practices and compliance with agency standards.