Job Title: Business Intelligence Analyst Specialist
Location: Austin, TX [ Onsite ]
Onsite 5 days a week
C2C fine
Need locals only
Responsibilities
o Work with program areas and project sponsor to gather business requirements and translate into technical specifications.
o 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
o Translate complex data requests and operational requirements into clear, actionable queries for AI against complex analytics data sources.
o Explain technical findings and data limitations in simple, non-technical language to end-users.
- AI Prompting and Data Synthesis
o Develop and refine effective AI prompts and query strategies to retrieve and synthesize data accurately from complex datasets.
o Guide non-technical users in crafting precise prompts to get the data they need, ensuring fidelity and accuracy.
o Develop a library of standardized prompts and query templates for common reporting needs.
- Data Reporting and Visualization
o Extract, integrate, and analyze data from multiple complex internal and external sources to support program needs.
o 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.
o Provide subject matter expertise on validating output from AI, particularly with respect to identifying and mitigating hallucinations.
o Ensure all data outputs adhere to agency reporting standards, data governance, and compliance regulations.
- Data Literacy and Training
o Champion data literacy across the organization by developing and conducting AI training sessions for non-technical staff.
o Create clear, comprehensive documentation and tutorials on using AI tools for data synthesis.
o Promote a data-driven culture by enabling and empowering all employees to effectively utilize data and AI.
- Collaboration and Problem-Solving
o Work closely with data engineering, IT, and Program teams to troubleshoot data-related issues and address inconsistencies and mitigation strategies.
o Provide expert guidance to program staff on interpreting data trends and answering complex data questions.
o Stay up to date on new AI and data analytics tools and techniques to continuously improve data access, data quality and reporting.
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