• Lead analytical efforts to drive data informed decision-making across the entire organization • Gather, analyze, and visualize / present technical insurance data • Collaborate with data engineering, insurance product, claims, finance and operations teams to improve data integrity and automate reporting capabilities using VBA, SQL and Python • Transform complex insurance data into clear, compelling insights for both technical and non-technical stakeholders through required reporting and data visualization • Conduct deep-dive data analysis, develop analytical tools, deliver dedicated solutions to help other departments automate their workflows, and identify opportunities to enhance business performance and operational effectiveness • Provide ad hoc analytical support and research as needed to ensure Ledgebrook continues to operate with data-driven precision.

• Transform complex business data into meaningful insights that support strategic decision-making across the Credit Union. • Partner with business leaders to develop enterprise reporting solutions and identify trends and opportunities. • Deliver data-driven recommendations to improve operational performance and enhance the member experience. • Design, develop, and maintain enterprise Tableau dashboards, executive scorecards, and performance indicator (KPI) reporting. • Analyze large volumes of financial, operational, lending, and member data to identify trends and actionable business insights. • Present analytical findings through professional visualizations and executive-level presentations that facilitate informed decision-making. • Promote best practices related to data quality, reporting standards, and documentation.

• Partner with cross-functional teams, including Marketing, Finance, Product, Sales, Medical Affairs, and Customer Success, to understand business needs and deliver actionable analyses. • Proactively explore data to identify patterns, trends, and opportunities that can drive business growth and operational improvements. • Define and manage data collection requirements across systems and functions to support consistent reporting and insight generation. • Develop, optimize, and automate data pipelines using structured query language (SQL), artificial intelligence, and modern data engineering tools to deliver timely, accurate reporting at scale. • Build and maintain robust, interactive dashboards that enable self-service reporting across go-to-market and product teams. • Identify opportunities to improve processes, reduce manual work, and drive efficiencies across the data landscape. • Translate complex data into clear, compelling visualizations and presentations for diverse audiences, including executives and external partners. • Partner with data scientists, analysts, and engineers to improve data quality, reporting accuracy, and analytical consistency across the organization.

• Extract and consolidate data from multiple systems using SQL and other data access tools. • Design and implement standardized data models across key business processes and financial metrics. • Develop and maintain dashboards and reporting (primarily in Power BI) supporting both operational and financial performance. • Translate business and FP&A needs into actionable analytics and visualizations. • Support process improvement and integration initiatives with data analysis. • Identify trends, anomalies, and root causes of operational and financial performance issues. • Establish processes to ensure data accuracy, completeness, and consistency. • Monitor and improve data quality across systems and reporting outputs.