Business Intelligence - Advanced Analytics - Vice President

Make your mark modernizing business intelligence with artificial intelligence-driven insights, enterprise visibility, and strong career mobility.

As a Business Intelligence — AI & Advanced Analytics Vice President within Commercial Investment Banking, you will lead a high-velocity function that converts data into decisions, balancing approximately 60% hands-on delivery with 40% strategic leadership. You will partner closely with Data Engineering to build governed logical and semantic layers, elevate visualization in Sigma and Tableau, and operationalize large language model-powered natural language querying through tools such as Databricks Genie. You will measure success through decision velocity, adoption, and return on investment, anchored by an insight-to-action governance model that assigns ownership and tracks outcomes.

Job Responsibilities

• Partner with senior and executive stakeholders to align analytics priorities to strategy, surface forward-looking insights, and influence outcomes through strong engagement.
• Drive end-to-end delivery across the analytics lifecycle, from problem framing and success criteria through user acceptance testing, deployment, adoption, and impact measurement with clear ownership and service-level agreements.
• Architect and govern the semantic layer by defining logical structures, business rules, and metric definitions for Engineering to implement, while coaching modeling trade-offs and performance optimization.
• Implement artificial intelligence-enabled business intelligence by enabling natural language querying (for example, Databricks Genie), designing domain-specific assistants, and embedding predictive analytics into decision flows as maturity grows.
• Establish visualization standards and personally build and review high-impact Sigma and Tableau assets that emphasize usability, performance, and guided analysis.
• Run an insight-to-action governance model that prioritizes findings, assigns accountable owners, tracks outcomes to closure, and communicates benefits, trade-offs, and risks transparently.
• Quantify and track portfolio impact metrics including adoption, decision velocity, decision quality, and return on investment, applying disciplined risk-adjusted prioritization.
• Orchestrate change management and enablement to drive adoption, including training, quick-reference content, and executive-ready briefings.
• Develop team capability through upskilling, code and modeling reviews, visualization critiques, and recruiting hybrid talent with domain and technical depth.
• Refine a continuous improvement backlog by iterating post go-live based on feedback and decommissioning low-value artifacts.

Required qualifications, skills, and capabilities

• Demonstrate 10+ years of experience delivering business intelligence or analytics solutions.
• Show 3+ years of leadership delivering enterprise-scale business intelligence capabilities with measurable outcomes.
• Apply mastery of logical and semantic data modeling, semantic layer design, and metric stewardship.
• Build and optimize Sigma and Tableau assets, including performance tuning, governed self-service, and row-level security.
• Write advanced SQL (Structured Query Language) to analyze, validate, and troubleshoot complex datasets.
• Develop Python solutions to support analytics delivery, automation, or data quality use cases.
• Operationalize large language models and natural language processing within business intelligence workflows, including prompt engineering and Databricks Genie.
• Govern data definitions and metadata through disciplined documentation and stewardship practices.
• Use applied statistics and hypothesis testing to support sound measurement and decision-making.
• Translate ambiguous stakeholder asks into precise analytical requirements, success criteria, and testable outcomes.
• Communicate executive-ready narratives that translate complex analytics into actionable, well-controlled decisions while influencing cross-functional partners.

Preferred qualifications, skills, and capabilities

• Deploy natural language querying over governed data in a way that supports scalable adoption and consistent metric interpretation.
• Build domain-specific artificial intelligence assistants aligned to business taxonomy and governed metric definitions.
• Drive adoption at scale with measurable return on investment and outcome tracking tied to decision-making.

Demonstrated ability to identify opportunities for AI and automation integration within operational workflows, including experience evaluating, implementing, or governing AI-driven solutions to achieve scalable process improvements and strategic objectives.