AI Finance Manager – Data Strategy & Gen AI

EY; Akron (OH); On-site; USD 143,000 - 285,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off options

Job summary

EY is seeking an AI Finance Manager to support data management for finance applications, leveraging expertise in planning, reporting, and close/consolidation. You will work with Gen AI and Azure to design an extensible data model and ensure data consistency across applications.

You will collaborate with the Data Lead and Product Owner to implement the FDL Blueprint, deliver scalable architectures, and maintain documentation across data dictionaries and data lineage maps.

Qualifications

• Bachelor’s degree in Finance, Accounting, Business, or Computer Science.
• Minimum of five years of progressive FP&A experience with planning, budgeting, forecasting, and reporting.
• Strong proficiency with EPM platforms: Anaplan, Oracle EPM Cloud Suite, Oracle Hyperion, OneStream/Tagetik.
• Knowledge of financial data architecture, governance, and master data management.
• Ability to travel to meet client needs.

Responsibilities

• Lead design and delivery of system architecture solutions with technical teams.
• Tailor platforms to business processes, maximizing investment and enabling continuous improvement.
• Manage complex processes and projects with a focus on quality and risk.

Skills

Data management

Data governance

Data architecture

Data modeling

Master data management

Machine Learning

Gen AI

Azure technologies

Leadership

Client engagement

Education

Bachelor's degree in Finance, Accounting, Business, CS

Tools

Anaplan

Oracle EPM Cloud Suite

Oracle Hyperion

OneStream

Tagetik

Job description

EY is seeking an AI Finance Manager to support data management for finance applications, leveraging expertise in planning, reporting, and close/consolidation. You will work with Gen AI and Azure to design an extensible data model and ensure data consistency across applications.

You will collaborate with the Data Lead and Product Owner to implement the FDL Blueprint, deliver scalable architectures, and maintain documentation across data dictionaries and data lineage maps.