AI Finance - Manager - Tech Consulting

AI Finance Manager – Tech Consulting

Location:

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, 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.

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) coupled with advanced skills in enterprise data management, data governance, data quality, master data management, Machine Learning, and Generative AI (Gen AI) to support key finance personas.

• 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.
• Support the effective management and utilization of finance application data, harnessing Machine Learning, Gen AI, and Azure data technologies.
• Lead workstream delivery, ensuring processes and solutions are managed effectively while maintaining a focus on quality and risk management.
• Engage with clients daily, participate in planning and execution, and identify opportunities for additional services.

• Fostering relationships with client personnel at appropriate levels and consistently delivering quality client services.
• Monitoring progress, managing risk, and confirming that key stakeholders are kept informed.
• Managing expectations of client service delivery.
• Effectively managing and motivating client engagement teams with diverse skills and backgrounds.
• Fostering an innovative and inclusive team‑oriented work environment.
• Supporting Data Management Strategy Execution for finance applications.
• Collaborating with cross‑service line teams to ensure alignment and integration of finance application data.
• Defining data requirements, architecture, and models for finance applications considering Machine Learning and Gen AI.
• Leading the design and implementation of an extensible common information model for the FDL Blueprint.
• Developing and maintaining documentation, including data dictionaries, entity‑relationship diagrams, and data lineage maps.
• Leading the development and implementation of our FDL Blueprint solution offering, ensuring scalability, performance, and security.
• Collaborating with data scientists and finance SMR’s across service lines to apply Machine Learning and Gen AI techniques to finance applications/personas.
• Supporting the establishment and maintenance of a robust data governance framework for the FDL.
• Staying current with the latest advancements in Machine Learning, Gen AI, Data Management, and Azure technologies.

• A bachelor’s degree and approximately five years of related work experience; or a graduate degree and approximately four years of related work experience.
• Minimum of 4 years of experience in data management, with at least 1 year focused on finance application data, data modeling, and financial modeling.
• Strong understanding of data management principles, including data governance, data quality, and master data management.
• Experience with Machine Learning techniques, Gen AI technologies, and Azure data services (e.g., Azure Data Lake, Azure Synapse Analytics, MS SQL,…