• Designing, developing, and maintaining business data and statistical models • Developing insightful KPI reporting dashboards to drive decision-making and performance tracking • Developing reports and dashboards via data mining analytics and reporting tools • Preparing analytics reports in presentation form • Assisting in developing sound data ETL practices and processes • Conducting research and analyze special studies when needed • Creating and updating documentation of process flows and business rules • Maintaining current reports up to date and processing large amounts of data as needed

• Partner with internal teams to understand business needs, analyze data, and support informed decision‑making • Prepare and analyze datasets, develop clear visualizations, and communicate insights • Apply analytics best practices, including data quality, documentation, reproducibility, and appropriate metric use • Manage and deliver analytics projects, ensuring clear timelines, communication, and stakeholder alignment • Collaborate with stakeholders to clarify business questions and recommend relevant analyses, metrics, or KPIs • Prepare, clean, and transform datasets—including large or complex data—using effective blending, validation, and refinement techniques • Conduct intermediate statistical analyses to identify trends, patterns, and drivers • Create accessible and meaningful visualizations using tools such as Tableau or Power BI, tailoring outputs to audience needs • Integrate data and visuals from multiple sources to communicate clear, actionable insights • Lead small or operational analytics efforts, including scoping, task planning, progress tracking, and risk escalation • Support team members through peer reviews, shared resources, and collaborative problem‑solving • Maintain awareness of customer needs, market context, and how business changes affect data interpretation • Use approved AI tools to streamline routine analytics tasks while ensuring accuracy and completeness

• Apply analytics best practices, including data quality, documentation, reproducibility, and appropriate metric use. • Manage and deliver analytics projects, ensuring clear timelines, communication, and stakeholder alignment. • Collaborate with stakeholders to clarify business questions and recommend relevant analyses, metrics, or KPIs. • Prepare, clean, and transform datasets—including large or complex data—using effective blending, validation, and refinement techniques. • Conduct intermediate statistical analyses to identify trends, patterns, and drivers. • Create accessible and meaningful visualizations using tools such as Tableau or Power BI, tailoring outputs to audience needs. • Integrate data and visuals from multiple sources to communicate clear, actionable insights. • Lead small or operational analytics efforts, including scoping, task planning, progress tracking, and risk escalation. • Support team members through peer reviews, shared resources, and collaborative problem‑solving. • Maintain awareness of customer needs, market context, and how business changes affect data interpretation. • Use approved AI tools to streamline routine analytics tasks while ensuring accuracy and completeness.

• Design and deliver dashboards with BI tools that bring clarity and vision to stakeholders • Use SQL and Excel to explore data, reveal trends, and extract actionable findings • Partner with cross-functional teams to deliver data-driven solutions to real business challenges • Ensure data accuracy, consistency, and structure across all databases • Troubleshoot data issues with agility and deliver timely resolutions • Validate, clean, and interpret datasets from multiple sources to tell a reliable story