Senior AI Finance Data Architect & GenAI Lead

EY; New Orleans (LA); Vor Ort; USD 103.000 - 188.000; Vollzeit

Benefits dieser Stelle

Medical and dental coverage

401(k) with pension

Zusammenfassung

EY is seeking an Al Finance Senior to support the Finance Applications Data Lead in executing data management strategies for finance applications. You will leverage depth in finance apps (planning, reporting, close/consolidation) with enterprise data management, governance, quality, and ML capabilities to shape EY's Finance Data Landscape.

The role focuses on developing the EY Al Finance service offering and creating an industry-agnostic data model, ensuring data consistency across finance

Qualifikationen

• Bachelor's degree or graduate degree with related work experience.
• 2+ years data management experience, 1+ year on finance data.
• Strong understanding of data governance, data quality, and master data management.
• Experience with ML techniques, Gen AI, and Azure data services.
• Knowledge of finance applications including financial modeling.

Aufgaben

• Gather and analyze business requirements; translate into technical specs.
• Collaborate with technical teams to design and deliver system architecture solutions.
• Define data requirements, architecture, and models for finance applications.

Kenntnisse

Data management

Machine Learning

Gen AI

Azure data services

Data governance

Data modeling

Finance applications

Communication

Problem-solving

Cross-team collaboration

Ausbildung

Bachelor's degree

Graduate degree

Tools

Azure Data Lake

Azure Synapse Analytics

MS SQL

Python

Jobbeschreibung

EY is seeking an Al Finance Senior to support the Finance Applications Data Lead in executing data management strategies for finance applications. You will leverage depth in finance apps (planning, reporting, close/consolidation) with enterprise data management, governance, quality, and ML capabilities to shape EY's Finance Data Landscape.

The role focuses on developing the EY Al Finance service offering and creating an industry-agnostic data model, ensuring data consistency across finance