AI Finance - Manager - Tech Consulting - Location Open

About the role

The AI Finance Manager supports the Finance Applications Data Lead in executing the overall data management strategy for finance applications. Key responsibilities include developing and implementing the EY AI Finance service offering, focusing on creating an industry-agnostic data model for finance applications.

Responsibilities

• Supports the effective management and utilization of finance application data
• Leverages Machine Learning, Gen AI, and Azure data technologies to drive innovation and business value
• Collaborates with finance, IT, and data science teams to ensure the successful delivery of projects
• Ensures accountability for performance and results in complex technical initiatives
• Designs and delivers system architecture solutions
• Identifies innovative solutions through research and analysis to drive continuous process improvement

Requirements

• A bachelor's degree and approximately five years of related work experience; or a graduate degree in the same with 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, 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, 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, supporting the adoption and implementation of emerging technologies

Qualifications

• Passionate leader with strong vision and a desire to stay on top of trends in the analytics industry
• Genuine passion for helping businesses achieve the full potential of their data

Skills

• Fostering relationships with client personnel at appropriate levels
• Maintaining quality client services
• Managing risk and keeping stakeholders informed
• Managing client engagement teams with diverse skills and backgrounds
• Providing constructive feedback and coaching
• Fostering an innovative and inclusive team-oriented work environment
• Supporting Data Management Strategy Execution
• Collaborating with cross-service line teams, including Finance, Managed Services, and Tech Consulting
• Defining data requirements, data architecture, and data models for finance applications
• 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 the FDL Blueprint solution offering
• Collaborating with data scientists and finance SMR’s across service lines
• 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

Benefits

To qualify for the role, you must have:

• A bachelor's degree and approximately five years of related work experience; or a graduate degree in the same with 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, 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, 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, supporting the adoption and implementation of emerging technologies