AI Finance - Senior - Tech Consulting - Location Open

About the role

The AI Finance Senior plays a crucial role in supporting the Finance Applications Data Lead in executing the overall data management strategy for finance applications. This role leverages deep expertise in finance applications, data management, and machine learning to support key finance personas.

Responsibilities

• Develop and implement EY's AI Finance service offering, focusing on creating an industry-agnostic data model for finance applications.
• Work closely with the Data Lead and Product Owner for the EY AI Finance solution to ensure the blueprint is designed on a solid foundation of finance application data architecture.
• Interact with business stakeholders to evaluate business models, processes, and operations, gathering and analyzing business requirements and translating them into technical specifications.
• Provide in-depth analysis related to implementation, customization, and optimization of technology platforms, particularly in the context of machine learning and generative AI.
• Engage with business stakeholders to gather and analyze business requirements, collaborate with technical teams to design and deliver system architecture solutions, and tailor technology platforms to align with business processes and objectives.

Requirements

The successful candidate must have a bachelor's degree and approximately three years of related work experience in data management, with at least one year focused on finance application data, data modeling, and financial modeling. Strong understanding of data management principles, including data governance, data quality, and master data management, is essential. Experience with machine learning techniques, generative AI technologies, and Azure data services is required. Knowledge of finance applications, such as financial modeling (P&L, Balance Sheet, Cash Flow), and proficiency in data integration, data transformation, and data modeling tools are also necessary. Excellent communication, collaboration, and problem-solving skills are required, along with the ability to work effectively in a fast-paced, dynamic environment.

Qualifications

• Bachelor's degree or equivalent in Finance, Computer Science, Information Systems or a related field with relevant experience in finance data management, including data modeling and ML.
• Minimum of 2 years of experience in data management, with at least 1 year focused on finance application data.
• Strong understanding of data management principles, including data governance, data quality, and master data management.
• Experience with machine learning techniques, generative 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

• Fostering relationships with client personnel at appropriate levels.
• Consistently running and delivering quality client services.
• Driving high-quality work products within expected time frames and on budget.
• Monitoring progress, managing risk, and keeping key stakeholders informed about progress and expected outcomes.
• Managing expectations of client service delivery.
• Providing constructive on-the-job feedback/coaching to team members.
• Fostering an innovative and inclusive team-oriented work environment.
• Playing an active role in the counseling and mentoring of junior consultants within the organization.
• Supporting data management strategy execution, including helping execute the overall data management strategy for finance applications.
• Collaborating 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.
• Defining data requirements, data architecture, and data models for finance applications, considering the potential of machine learning and generative AI technologies.
• 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 our FDL Blueprint solution offering, ensuring scalability, performance, and security.
• Sustaining collaboration with data scientists and finance SMEs across service lines to identify opportunities for applying machine learning and generative AI techniques to finance applications/personas and extend the FDL.
• Supporting the establishment and maintenance of a robust data governance framework for the FDL.
• Staying current with the latest advancements in machine learning, generative AI, data management, and Azure technologies and identifying and implementing innovative solutions that drive efficiency, accuracy, and insights for finance applications.

Pay

The base salary range for this role in the US is $102,500 to $187,900, with a higher range for New York City Metro Area, Washington State, and California (excluding Sacramento).

Schedule

This role may require regular travel to meet with clients and participate in project activities.