AI Finance - Senior Manager - Tech Consulting

AI Finance - Senior Manager - Tech Consulting

Join EY to apply for the AI Finance Senior Manager role in our Tech Consulting practice. This position is open across multiple U.S. locations.

Chicago, Akron, Arlington, Atlanta, Austin, Baltimore, Birmingham, Boca Raton, Boston, Buffalo, Charleston, Charlotte, Chattanooga, Cincinnati, Cleveland, Columbia, Columbus, Dallas, Denver, Des Moines, Detroit, Edison, Fort Worth, Grand Rapids, Greenville, Hartford, Hoboken, Honolulu, Houston, Indianapolis, Irvine, Jacksonville, Kansas City, Los Angeles, Las Vegas, Louisville, McLean, Memphis, Miami, Milwaukee, Minneapolis, Nashville, New Orleans, New York, Oklahoma, Orlando, Palo Alto, Philadelphia, Phoenix, Pittsburgh, Pleasanton, Portland, Providence, Raleigh, Richmond, Rochester, Rogers, Sacramento, Salt Lake City, San Antonio, San Diego, San Francisco, San Jose, Seattle, Secaucus, Stamford, St.

Louis, Syracuse, Tallahassee, Tampa, Toledo, Tucson, Tulsa, Washington DC, Westlake Village, Winston-Salem.

The AI Finance Senior Manager is a crucial role responsible for supporting the Finance Applications Data Lead in executing the overall data management strategy for finance applications. Leveraging expertise in finance applications, enterprise data management, data governance, data quality, master data management, machine learning, and generative AI, you will develop and implement our FDL consulting blueprint to create an industry‑agnostic data model that ensures data consistency and interoperability across finance applications.

You will work closely with the Data Lead and Product Owner to ensure the blueprint is built on reliable finance application data architecture, enabling informed decision‑making.

• Lead the design and delivery of system architecture solutions in collaboration with technical teams.
• Tailor technology platforms to business processes, ensuring clients maximize their investment through effective use and continuous improvement.
• Manage complex processes, solutions, and projects while maintaining a focus on quality and risk management.

• Proven ability to manage and deliver complex solutions.
• Foster relationships with client personnel at appropriate levels; consistently provide high‑quality client services.
• Monitor progress, manage risk, and keep stakeholders informed.
• Manage expectations of client service delivery.
• Effectively manage and motivate client engagement teams with diverse skills.
• Provide constructive coaching and foster an innovative, inclusive team environment.
• Support data management strategy execution for finance applications.
• Define data requirements, architecture, and models for finance applications, considering ML and Gen AI potential.
• Lead design and implementation of an extensible common information model for the FDL Blueprint.
• Develop and maintain documentation (data dictionaries, ER diagrams, data lineage maps).
• Ensure scalability, performance, and security of the FDL Blueprint solution.
• Collaborate with data scientists and finance SMRs across service lines to apply ML/Gen AI techniques to finance applications/personas.
• Support a robust data governance framework for the FDL.
• Stay current with advancements in ML, Gen AI, data management, and Azure technologies.
• Ability to travel as required for client engagements.

• Bachelor’s degree in Finance, Accounting, Business, or Computer Science.
• Minimum of seven years of progressive experience in FP&A, with demonstrated expertise in:
  • Strategic financial planning, budgeting, and forecasting.
  • Financial modeling and scenario analysis.
  • Variance analysis and management reporting.
  • Cross‑functional collaboration with business stakeholders.
• Strong proficiency with EPM platforms, including hands‑on experience with Anaplan, Oracle EPM Cloud Suite, Oracle Hyperion, One Stream, Tagetik, or similar.
• Solid understanding of financial data architecture and governance, including:
  • Financial data modeling and dimensional design.
  • Chart of accounts structuring and hierarchy management.
  • Data quality standards and reconciliation processes.
  • Master data management for finance applications.
• Excellent…