AI Finance - Manager - Tech Consulting - Location Open
About the Role
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. This role leverages deep expertise in finance applications (planning, reporting, close/consolidation) and enterprise data management to support key finance personas. A key responsibility is developing and implementing the EY AI Finance service offering, creating an industry-agnostic data model to ensure data consistency and interoperability across finance applications.
Responsibilities
- 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 execution of the overall data management strategy for finance applications.
- Collaborate with cross-service line teams to ensure alignment and integration of finance application data.
- Define data requirements, data architecture, and data models for finance applications, considering Machine Learning and Gen AI technologies.
- 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.
- Lead the development and implementation of the FDL Blueprint solution offering, ensuring scalability, performance, and security.
- Collaborate with data scientists and finance SMR’s to apply Machine Learning and Gen AI techniques to finance applications.
- Support the establishment and maintenance of a robust data governance framework for the FDL.
- Stay current with advancements in Machine Learning, Gen AI, Data Management, and Azure technologies.
Qualifications
- 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 and data 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, Python).
- Knowledge of finance applications including financial modeling (PnL, Balance Sheet, Cash Flow).
- Proficiency in data integration, data transformation, and data modeling tools and techniques.
- Excellent communication, collaboration, and problem-solving skills.
- Ability to work effectively in a fast-paced, dynamic environment.
Preferred Qualifications
- Degree in Finance, Computer Science, Information Systems, or a related field with relevant experience in finance data management, including data modeling and ML.
Skills
- Fostering relationships with client personnel at appropriate levels.
- Delivering quality client services within expected time frames and on budget.
- Monitoring progress, managing risk, and keeping stakeholders informed.
- Managing and motivating diverse client engagement teams.
- Providing constructive feedback and coaching to team members.
- Fostering an innovative and inclusive team-oriented work environment.
- Counseling and mentoring junior consultants.
Pay
The base salary range for this job in all geographic locations in the US is $142,600 to $261,500. The base salary range for New York City Metro Area, Washington State, and California (excluding Sacramento) is $171,200 to $297,200. Individual salaries are determined through factors including education, experience, knowledge, skills, and geography.
Benefits
- Comprehensive compensation and benefits package.
- Medical and dental coverage.
- Pension and 401(k) plans.
- Flexible vacation policy.
- Paid time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence.
Schedule
Our expectation is for most people in external, client-serving roles to work together in person 40-60% of the time over the course of an engagement, project, or year, in a team-led and leader-enabled hybrid model.