AI Finance - Senior - Tech Consulting

AI Finance - Senior - Tech Consulting - Location Open

Join EY as a Senior AI Finance – Tech Consulting specialist. You will support the Finance Applications Data Lead in executing the overall data management strategy for finance applications.

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 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‑S‑alem

The AI Finance Senior is a crucial role responsible for supporting the Finance Applications Data Lead in executing the overall data management strategy for finance applications. You will leverage deep expertise in finance applications (planning, reporting, close/consolidation) along with enterprise data management, data governance, data quality, master data management, Machine Learning and Generative AI (Gen AI).

• Engage with business stakeholders to gather and analyze business requirements.
• Collaborate with technical teams to design and deliver system architecture solutions.
• Tailor technology platforms to align with business processes and objectives.

• Fostering relationships with client personnel, delivering quality client services on time and within budget.
• Monitoring progress, managing risk, and keeping stakeholders informed.
• Managing expectations of client service delivery.
• Effectively managing and motivating client engagement teams.
• Supporting Data Management Strategy Execution for finance applications.
• Collaborating with cross‑service line teams.
• Defining data requirements, architecture, and models for finance applications.
• Leading design and implementation of an extensible common information model.
• Developing and maintaining documentation (data dictionaries, ER diagrams, lineage maps).
• Ensuring scalability, performance, and security of the FDL Blueprint solution.
• Collaborating with data scientists to apply ML and Gen AI techniques to finance applications.
• Supporting a robust data governance framework for the FDL.
• Staying current with advancements in ML, Gen AI, Data Management, and Azure technologies.

• A bachelor’s degree and approximately three years of related work experience; or a graduate degree in the same field and approximately two years of related work experience.
• Minimum of 2 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 (governance, quality, master data).
• Experience with Machine Learning techniques, Gen AI technologies, and Azure data services (Azure Data Lake, Azure Synapse Analytics, MS SQL, Python).
• Knowledge of finance applications and financial modeling (PnL, Balance Sheet, Cash Flow).
• Proficiency in data integration, transformation, and modeling tools and techniques.
• Excellent communication, collaboration, and problem‑solving skills.
• Ability to work effectively in a fast‑paced, dynamic environment.

• Degree in Finance, Computer Science, Information Systems or a related field with experience in finance data management including data modeling and ML.

• Comprehensive compensation and benefits package with base salary range $102,500 to $187,900 (range varies by location). Total rewards include medical, dental, pension, 401(k), paid time off.
• Flexible hybrid work model: 40–60% in‑person for client‑serving roles.
• Flexible vacation policy.