AI Finance - Senior - Tech Consulting - Location Open

About the role

The AI Finance Senior role 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

• Support the Finance Applications Data Lead in executing the overall data management strategy for finance applications.
• Leverage deep expertise in finance applications (planning, reporting, close/consolidation), data management, data governance, data quality, master data management, Machine Learning, and Generative AI (Gen AI).
• Work closely with the Data Lead and Product Owner for the EY AI Finance solution to ensure the EY AI Finance Blueprint is designed on a foundation of accurate, consistent, and reliable finance application data architecture.
• Interact with business stakeholders to evaluate business models, processes, and operations, gathering, understanding, and analyzing business requirements, and translating them into technical specifications.
• Provide in-depth analysis related to implementation, customization, and optimization of specific technology platforms.
• 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.

Requirements

• A bachelor's degree and approximately three years of related work experience; or a graduate degree in the same 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, 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.

Skills and Attributes

• Foster relationships with client personnel at appropriate levels.
• Drive high-quality work products within expected time frames and on budget.
• Monitor progress, manage risk, and keep key stakeholders informed about progress and expected outcomes.
• Manage expectations of client service delivery.
• Provide constructive on-the-job feedback/coaching to team members.
• Foster an innovative and inclusive team-oriented work environment.
• Play an active role in the counseling and mentoring of junior consultants within the organization.
• Support Data Management Strategy Execution, including helping execute the overall data management strategy for finance applications.
• Collaborate with cross-service line teams, including Finance, Managed Services, and Tech Consulting to ensure alignment and integration of finance application data with related data initiatives.
• Define data requirements, data architecture, and data models for finance applications, considering the potential of 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.
• Develop and implement our FDL Blueprint solution offering, ensuring scalability, performance, and security.
• Support the establishment and maintenance of a robust data governance framework for the FDL.
• Stay current with the latest advancements in Machine Learning, Gen AI, Data Management, and Azure technologies and identify and implement innovative solutions that drive efficiency, accuracy, and insights for finance applications.

Qualifications

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