Analyst

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Description

This role sits at the intersection of Finance, Data, and AI, enabling the transformation of finance data into a strategic, intelligence-driven asset. It supports the design, governance, and activation of finance data capabilities to deliver faster insights, improved decision-making, and scalable business value.

The role will drive adoption of modern data platforms, while actively exploring and embedding GenAI and agentic solutions to automate workflows, enhance analytics, and enable intelligent, self-service finance operations. Working closely with Finance and Digital Technology teams, this position contributes to building an AI-enabled finance ecosystem that is standardized, efficient, and future-ready.

Job Overview and Responsibilities

1. Support Enterprise-Wide Data Standards, Analytics, and Insights

• Support cross-functional collaborations to assess and redesign finance data processes and technical landscapes, focusing on simplification, standardization, and end-to-end optimization aligned with enterprise goals
• Work with large and complex (big) data sets across finance domains, ensuring scalable handling, efficient processing, and performance optimization across systems and data platforms
• Evaluate and embed GenAI and agentic solutions (e.g., copilots, autonomous workflows, intelligent pipelines) to reimagine finance processes, reduce manual effort, and accelerate decision-making cycles
• Drive adoption of modern data and automation tools (Data Platforms, Oracle, Alteryx, Power BI), augmenting them with AI-driven insights, predictive analytics, and intelligent automation
• Develop and maintain financial data products, standardized KPIs, reusable datasets, and robust, dynamic data structures (e.g., scalable data models, semantic layers) to support evolving business needs and AI consumption
• Maintain and validate finance data mappings, transformation logic, and integrations, while exploring AI-assisted reconciliation, mapping automation, and anomaly detection
• Support finance data governance by defining data quality rules and partnering on controls and lineage, leveraging AI for continuous monitoring, exception handling, and automated remediation insights

2. Support financial transformation initiatives

• Collaborate cross-functionally to support finance data transformation initiatives, incorporating AI-first design principles, scalable data structures, and automation opportunities into solution architecture