VP, Enterprise Analytics and AI Strategy

Midwest BankCentre•St. Louis, MO

About The Position

The Vice President, Enterprise Analytics and AI Strategy is a strategic enterprise leader responsible for shaping and advancing the organization’s analytics, data, and AI agenda. This role leads the development of a modern, scalable analytics ecosystem that enables better decision-making, improves operational performance, strengthens client and stakeholder outcomes, and creates long-term enterprise value. This executive will be responsible for transforming data into a strategic asset by building trusted platforms, aligning cross-functional stakeholders, and embedding analytics into the fabric of the organization. The role requires a unique combination of business insight, strategic leadership, technical fluency, change management capability, and strong communication skills. The VP, Enterprise Analytics and AI Strategy will help the organization move from fragmented reporting toward an integrated, forward-looking model that includes business intelligence, predictive insights, data governance, automation, and artificial intelligence. In addition to leading enterprise analytics, this role will help define and drive the organization’s AI transformation roadmap, identifying practical and responsible ways to use AI to improve decision-making, increase efficiency, enhance client experience, and unlock new business value. As the enterprise’s data and analytics capabilities mature, this leader will also help assess and shape opportunities to commercialize or monetize analytics assets, insights, products, or capabilities where strategically appropriate. This role partners closely with business leaders, technology teams, risk and compliance partners, and external stakeholders to ensure the organization’s analytics and AI strategy is aligned with business priorities, governance expectations, and long-term growth objectives.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Business Analytics, Statistics, Engineering, or a related field required; Master’s degree preferred.
Minimum of 10 years of progressive experience in analytics, business intelligence, data strategy, data management, or related functions, including significant leadership experience in enterprise-scale environments.
Minimum of 5 years of experience leading cross-functional teams and enterprise initiatives involving data, analytics, reporting, platform modernization, or digital transformation.
Demonstrated success developing and executing enterprise analytics strategies that align with business priorities and improve decision-making, performance, and operational efficiency.
Experience leading or enabling AI, automation, or advanced analytics initiatives, including identification of use cases, implementation planning, governance, and value realization.
Strong knowledge of modern data and analytics ecosystems, including business intelligence platforms, cloud data environments, data warehouses, data lakes, and enterprise reporting architectures.
Strong background in data visualization and business intelligence tools such as Power BI, Tableau, Looker, or similar platforms.
Experience with data modeling, forecasting, statistical analysis, predictive analytics, and performance measurement frameworks.
Strong working knowledge of SQL and data querying/manipulation techniques; familiarity with Python, R, or other analytics/programming languages preferred.
Experience establishing or advancing data governance, data quality, metadata, and data stewardship practices across an organization.
Understanding of privacy, regulatory, compliance, model risk, and information security considerations related to analytics and AI.
Ability to translate business strategy into an actionable analytics and AI roadmap, including prioritization of initiatives, platform investments, and operating models.
Demonstrated ability to communicate complex analytical, technical, and AI-related concepts to executive, operational, and non-technical audiences in a clear and actionable way.
Experience building enterprise dashboards, management reporting, and self-service analytics capabilities that support adoption and data literacy.
Ability to evaluate emerging tools, technologies, and external partnerships to strengthen the organization’s analytics and AI capabilities.
Strategic mindset with the ability to identify longer-term opportunities to create enterprise value through data assets, analytics products, decision-support tools, or other monetizable insights where appropriate.
Strong organizational, project leadership, and change management skills, with the ability to lead multiple priorities in a dynamic environment.
High level of professionalism, executive presence, sound judgment, and ethical standards in handling confidential and sensitive information.
Excellent oral, written, and interpersonal communication skills, with the ability to influence senior leaders and build alignment across business and technology teams.
Demonstrated commitment to innovation, continuous improvement, talent development, and building high-performing teams.

Nice To Haves

Master’s degree preferred.
familiarity with Python, R, or other analytics/programming languages preferred.

Responsibilities

Develops and leads the enterprise analytics strategy, establishing a clear roadmap that aligns data, analytics, and AI capabilities with the organization’s strategic priorities.
Builds and advances a modern enterprise analytics function that improves information delivery, supports decision-making, and enables measurable business outcomes across all lines of business.
Owns and standardizes enterprise decisioning frameworks, ensuring analytics is embedded in critical business processes including customer acquisition, pricing, risk management, and performance optimization.
Drives measurable impact on revenue growth, client primacy, deposit and loan growth, product penetration, and operational efficiency through analytics and AI initiatives.
Leads enterprise-wide efforts to align business leaders, technology partners, and data stakeholders around a common vision for analytics, reporting, platform development, and data enablement.
Serves as the senior leader and primary point of accountability for enterprise analytics initiatives, ensuring priorities are sequenced appropriately and resources are aligned to deliver value.
Drives the design, implementation, and continuous enhancement of scalable analytics platforms, dashboards, visualizations, and self-service reporting tools that make data accessible, useful, and actionable for both technical and non-technical users.
Champions the organization’s AI transformation efforts by identifying, prioritizing, and advancing responsible use cases for artificial intelligence, machine learning, and automation to improve business performance, client experience, and workforce productivity.
Partners with business and technology leaders to move the organization from descriptive reporting toward predictive and prescriptive analytics, enabling more proactive, forward-looking decision-making.
Establishes and maintains strong data governance, data quality, metadata, and analytics standards to ensure the integrity, consistency, security, and usability of enterprise data assets.
Ensures that analytics and AI practices are developed and deployed in compliance with applicable privacy, regulatory, risk, model governance, and information security requirements.
Works closely with IT and business units to architect and implement analytics and data solutions that improve operational efficiency, support strategic initiatives, and reduce fragmentation across systems and reporting environments.
Defines and tracks enterprise metrics, KPIs, and value-realization measures to assess the effectiveness, adoption, and business impact of analytics and AI initiatives.
Promotes data literacy and responsible AI literacy across the organization through training, communication, and change management efforts that build confidence and capability among leaders and teams.
Works with key stakeholders to embed analytics into frontline workflows, systems, and performance management routines to drive consistent adoption, behavior change, and measurable business outcomes.
Leads, develops, and inspires a high-performing team of analytics, business intelligence, data, and technology professionals, creating a culture of collaboration, innovation, accountability, and continuous improvement.
Evaluates emerging technologies, tools, and external partnerships to ensure the organization remains current and competitive in analytics, data engineering, visualization, and AI capabilities.
Helps the organization identify and assess longer-term opportunities to monetize analytics capabilities, data products, decision-support tools, or market-facing insights, where appropriate and consistent with strategy, regulation, and client trust.
Advises executive leadership on how analytics and AI can be used not only to support internal performance, but also to create differentiation, improve market responsiveness, and unlock new sources of enterprise value.