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Team
EY Strategy Execution & Operations (SE&O)
Role Title(s)
Senior Analyst - FS Audit Intelligence, Analytics & Automation
The Role
Senior Analyst - GFS Audit Intelligence, Analytics & Automation serves as a strategic enabler of data-driven governance, audit intelligence, and process digitization. This role is responsible for delivering actionable insights, market intelligence, and automated reporting solutions that support audit fee pricing, audit rotation strategies, auditor market share analysis, and portfolio mix account governance and process.
Key responsibilities:
- Data Management: Demonstrates a technology-enabled continuous improvement mindset, proactively identifying opportunities to enhance processes, controls, and data management practices. Able to design and maintain structured, scalable, and well-governed data solutions that support evolving business needs, advanced analytics, and future AI-enabled capabilities.
- Technology capability: Strong experience managing large and complex datasets, including advanced Excel, Power BI, data transformation and automation tools (e.g., Python), with a solid understanding of data quality, governance, and reporting methodologies to support scalable analytics and insight generation.
- Analytics and insights: Establish and apply leading-practice analytical approaches to assess audit fees, auditor rotations, market share, and related financial metrics. Act as a trusted advisor on benchmarking methodologies, data interpretation, and insight generation, ensuring analyses are consistent, defensible, and aligned with EY quality standards while supporting account strategy, governance, pursuits, and fee negotiations.
- Market and regulatory research: Perform market, regulatory, and auditor landscape research to validate data sources and methodologies, acting as a subject matter expert on external data providers and supporting the identification of credible, high-quality sources for business insights.
- Stakeholder management: Work closely with business stakeholders to understand priorities, translate requirements into actionable deliverables, and ensure outputs align with the objectives of GFS and Global Assurance leadership. Collaborate across internal teams to leverage existing knowledge, data, methodologies, and best practices to maximise the quality and impact of insights.
- Note: This above list of activities is not exhaustive but only gives an indication of the nature of the project / scope of work.
Research experience:
- Understanding of how to source and validate information from public sources
- Ability to investigate less structured information and identify new sources to expand knowledge and coverage
- Understand how to use tech to support research and data extraction with a mindset to evolve and automate at all times
- General understanding of financial institutions, corporate structures, subsidiaries and regulated entities
- Ability to interpret regulatory developments and assess their impact on our data set and insights
- Familiarity with financial reporting, governance disclosures, regulatory publications and public company filings
- Experience working with Financial Services, company, regulatory, market intelligence or comparable business datasets
- Awareness of audit-related information, including audit firms, audit fees and auditor appointments, although deep technical knowledge is not required
Tech skills:
- Advanced Excel skills, including advanced formulas, Pivot Tables, Power Query, Pivot, Macros and large dataset handling
- Data management - cleansing, reconciliation, validation and quality assurance methodologies
- Experience maintaining structured datasets and continuous improvement of efficiency and optimisation (data architecture knowledge desirable)
- Power BI skills – dashboard and visuals, data modelling, DAX knowledge
- Knowledge of Power Apps and Power Automate to support workflow automation, process improvement, and low-code solution development
- Python experience (desirable) - data analysis, transformation, validation and automation
- AI - understanding of AI and use of AI for improving automation of data collation / data management / insights
Data Architecture & Methodology:
- Experience developing analytical models and reporting outputs to support business decision-making
- Structured dataset and data model design, building scalable solutions that support future analytics and automation
- Data governance, documentation and control frameworks, consistent data standards, definitions and source management
- Understanding business objectives and keeping in front of mind when developing solutions and insights
- Continuous validation of deliverables against stakeholder requirements and evaluate how to evolve our solutions to support
To qualify for the role, you must have:
- Graduate / Post-graduate - (Business Administration, Information and Data Science) with 7 - 12 years’ work experience in professional services industry having exposure working on applications and automation.
- Strong understanding of data analytics, best practices when developing solutions and experience in solution development, specifically utilizing Microsoft suite of tools.
- Excellent communication and collaboration skills with the ability to work effectively with cross-functional teams.
What we look for:
- Exceptional attention to detail and quality focus.
- Curious, investigative, and solution oriented.
- Comfortable providing recommendations and evidence-based conclusions.
- Comfortable providing new tech solution ideas and improvements for data management and insights.
- Ability to translate analytical output into actionable recommendations for stakeholders and leadership.
- Strong ownership and accountability.
- Able to work independently with minimal supervision.
- Strong collaboration skills and a team-oriented mindset
- Reliable, proactive and consistent in delivery.
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