Senior Data & AI Analyst, Finance Systems

Worker Type

Job Description

 

Summary
The Senior Data & AI Analyst, Finance Systems owns financial data migration for Oracle Fusion implementation while pioneering the use of AI, large language models (LLMs), and intelligent agents to transform finance operations. This role combines traditional data conversion excellence with cutting-edge AI capabilities, building intelligent workflows for data quality, process automation, anomaly detection, and predictive analytics. This position reports directly to the Director, Finance Systems and serves as the technical lead for data and emerging AI initiatives.

Position Responsibilities

Finance Systems Data Operations & Migration

• Lead end-to-end data conversion planning for Oracle Fusion, including scope definition, data source identification, mapping specifications, and conversion schedules
• Extract, transform, and load financial data from legacy systems (Chart of Accounts, customer/vendor masters, open balances, historical transactions, asset registers)
• Develop and maintain data mapping documents that translate legacy data structures to Oracle Fusion Cloud data models (Procure to Pay, Record to Report, Quote to Cash, Project to Close)
• Execute iterative mock conversion cycles (Mock 1, Mock 2, Final) with progressively tighter quality gates and validation checkpoints
• Coordinate with IT Infrastructure team on technical data extraction, FBDI file generation, and API-based data loading

Data Quality, Validation & Analytics

• Design and implement comprehensive data quality rules, reconciliation controls, and exception handling processes; build automated validation scripts, profiling reports, and dashboards using Python, SQL, and AI/ML frameworks
• Partner with Accounting SMEs to validate converted balances, ensure trial balance integrity, and resolve discrepancies
• Develop predictive models for financial forecasting, anomaly detection in journal entries, and intelligent close process monitoring

AI/LLM & Intelligent Agent Development

• Design and build AI-powered intelligent agents using large language models (GPT, Claude, Gemini, or open-source alternatives) for finance process automation
• Develop LLM-based data quality agents that automatically detect anomalies, validate business rules, and suggest corrections during data migration and ongoing operations
• Create conversational AI interfaces for finance users to query data, generate reports, and troubleshoot issues through natural language
• Build intelligent document processing pipelines using LLMs for invoice extraction, contract analysis, and regulatory filing automation
• Implement prompt engineering frameworks, retrieval-augmented generation (RAG), fine-tuning strategies, and governance frameworks for responsible AI use including bias detection, explainability, and audit trails

EPM, Reporting & Data Governance

• Support data migration and integration for Oracle EPM Cloud (PBCS, FCCS, Planning) connecting to Oracle Fusion actuals and subledger data
• Troubleshoot reporting issues in Oracle Fusion (OTBI, BIP, Smart View, FBDI) and SplashBI, diagnosing data quality problems and performance bottlenecks
• Partner with FP&A and Accounting on EPM data flows, dimension hierarchies, and planning/forecasting data structures
• Support Apex application rollout through data integration, ensuring clean data pipelines between Apex, Fusion, and EPM environments
• Establish data governance frameworks for master data (COA, customers, vendors, projects) including ownership, quality rules, stewardship processes, data lineage documentation, and metadata repositories for regulatory compliance
• Support finance transformation projects through data analysis, migration support, and capitalization documentation

Cross-Functional Collaboration & Innovation

• Coordinate with Business Units, IT Infrastructure, and external vendors to secure data extracts, coordinate conversion windows, and troubleshoot technical issues
• Partner with Senior Manager, Finance Systems to align data conversion schedules with functional configuration timelines and testing cycles
• Evangelize AI/LLM capabilities across Finance organization through proof-of-concepts, workshops, lunch-and-learns, and documentation; build internal capability by training team members on effective LLM usage
• Maintain knowledge of emerging AI technologies, attend conferences/training, and share best practices through cross-team collaboration

Production Support, Post-Go-Live & Continuous Impro