AI Finance - Manager - Tech Consulting

AI Finance Manager – Tech Consulting

Join us to apply for the AI Finance Manager – Tech Consulting – Location Open role at EY
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Location:

Chicago, Akron, Arlington, Atlanta, Austin, Baltimore, Birmingham, Boca Raton, Boston, Buffalo, Charleston, Charlotte, Chattanooga, Chicago, Cincinnati, Cleveland, Columbia, Columbus, Dallas, Denver, Des Moines, Detroit, Edison, Fort Worth, Grand Rapids, Greenville, Hartford, Hoboken, Honolulu, Houston, Indianapolis, Irvine, Jacksonville, Kansas City, LA, Las Vegas, Louisville, McLean, Memphis, Miami, Milwaukee, Minneapolis, Nashville, New Orland, 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.

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

The AI Finance Manager is a crucial role responsible for supporting the Finance Applications Data Lead in executing the overall data management strategy for finance applications. The successful candidate will leverage deep expertise in finance applications (planning, reporting, close/consolidation) and skills in enterprise data management, data governance, data quality, master data management, Machine Learning, and Generative AI (Gen AI) to support key finance personas.

One of the key responsibilities is developing and implementing EY’s AI Finance service offering, with the goal of creating an industry-agnostic data model that can serve as a starting point and be extended to ensure data consistency and interoperability across finance applications.

The role involves interacting with business stakeholders, evaluating business models, processes, and operations, gathering requirements, translating them into technical specifications, and providing in-depth analysis related to implementation, customization, and optimization of specific technology platforms.

• Lead the delivery of complex technical initiatives, ensuring accountability for performance and results.
• Collaborate with technical teams to design and deliver system architecture solutions.
• Drive continuous process improvement by identifying innovative solutions through research and analysis.
• Lead the design and implementation of an extensible common information model for the FDL Blueprint.
• Develop and maintain documentation, including data dictionaries, entity-relationship diagrams, and data lineage maps.
• Collaborate with data scientists and finance SMRs across service lines to identify opportunities for applying Machine Learning and Gen AI techniques to finance applications/personas and extend the FDL.
• Support the establishment and maintenance of a robust data governance framework for the FDL.
• Stay current with the latest advancements in Machine Learning, Gen AI, Data Management, and Azure technologies, and identify and implement innovative solutions that drive efficiency, accuracy, and insights for finance applications.

• Fostering relationships with client personnel at appropriate levels; consistently running and delivering quality client services.
• Monitoring progress, managing risk, and confirming that key stakeholders are kept informed about progress and expected outcomes.
• Effectively managing and motivating client engagement teams with diverse skills and backgrounds; providing constructive on-the-job coaching.
• Fostering an innovative and inclusive team-oriented work environment; playing an active role in counseling and mentoring junior consultants.
• Supporting Data Management Strategy execution, including executing the overall data management strategy for finance applications.
• Collaborating with cross-service line teams to ensure alignment and integration of finance application data with related data initiatives.
• Defining…