AVP Business Intelligence

The Assistant Vice President of Business Intelligence provides enterprise leadership for Blaze Credit Union's business intelligence, analytics, and performance reporting capabilities. This role guides and supports the vision, priorities, standards, and operating model that transform data into timely, trusted, and actionable insights for executive, strategic, and operational decision-making.

As a leader and trusted advisor, the AVP partners across the Credit Union to align analytics investments with organizational priorities, strengthen data literacy, advance self-service reporting, and ensure business intelligence solutions deliver measurable value. The role balances strategic leadership, technical depth, disciplined execution, and clear communication while promoting responsible, secure, and ethical use of data and artificial intelligence.

Full-time, on-site at our Westminster administrative office in St Paul, MN

• Develop and execute an enterprise business intelligence and analytics strategy aligned with organizational goals, member needs, and business priorities.
• Establish a multi-year roadmap for reporting, dashboards, advanced analytics, and decision-support capabilities.
• Identify and prioritize high-value analytics opportunities based on strategic impact, feasibility, risk, and organizational readiness.
• Advise executive and senior leaders on performance trends, business implications, emerging opportunities, and data-informed options.
• Promote a culture in which leaders and teams consistently use data to frame questions, evaluate choices, and measure results.

• Provide leadership, direction, and accountability for business intelligence strategy in collaboration with key partners.
• Define clear roles, intake processes, service expectations, development standards, and delivery practices for business intelligence and predictive analytics.
• Build business intelligence capability in business acumen, data storytelling, visualization, analytical methods, stakeholder consultation, and emerging technologies.
• Plan and manage capacity, vendor relationships, budgets, and resources to support priority initiatives and sustainable delivery.
• Foster a collaborative, curious, inclusive, and results-oriented team environment.

• Lead the design and evolution of enterprise dashboards, scorecards, key performance indicators, and management reporting.
• Partner with leaders to define meaningful measures, targets, business definitions, and decision rights.
• Ensure business intelligence reporting is accurate, timely, relevant, intuitive, and appropriately tailored to executive, board, and operational audiences.
• Translate complex analysis into concise narratives, implications, and recommendations that support action.
• Establish processes to monitor adoption, usefulness, and business impact of business intelligence products.

• Guide descriptive, diagnostic, predictive, and prescriptive analytics that support growth, financial performance, member experience, risk management, and operational effectiveness.
• Oversee forecasting, scenario modeling, segmentation, trend analysis, and other analytical approaches used to inform enterprise decisions.
• Ensure analytical methods and models are appropriately designed, documented, validated, monitored, and communicated.
• Evaluate opportunities to use artificial intelligence, machine learning, and automation responsibly to improve insights and outcomes.
• Connect analytical findings to business context and recommend practical actions, tests, or follow-up analysis.

• Partner with Information Infrastructure and Technology, Data Governance, Risk, Compliance, and business leaders to strengthen data quality, access, security, lineage, and consistency.
• Establish and reinforce common definitions, documentation, certification standards, and controls for critical metrics and reporting assets.
• Identify material data limitations and quality concerns, communicate their business impact, and help prioritize remediation.
• Champion responsible and ethical data and AI practices, including appropriate privacy, transparency, model oversight, and human judgment.
• Ensure business intelligence practices comply with applicable laws, regulations, policies, and internal standards.

• Build strong relationships…