AI and Applied Analytics Lead

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Job Title: AI and Applied Analytics Lead

Experience Level: 10+ Years

Designation: Associate Director

The opportunity You will lead the development and scaling of

AI and analytics products within EY’s Global Insights function, equipping EY professionals with differentiated market, sector, and company insights that strengthen EY’s brand, deepen client relationships, and drive commercial impact. Working closely with EY Insights leadership, you will help shape our

long-term AI and analytics strategy , with a focus on building scalable, enterprise-grade solutions leveraging

Azure AI, modern data platforms, MLOps, and generative AI . As the

AI and Applied Analytics Lead , you will own a portfolio of AI and analytics products, self-serve tools, and proprietary models. These solutions combine

advanced analytics, machine learning, and large language models (LLMs) to deliver foundational intelligence at scale, uncover differentiated insights, and integrate with EY’s broader enterprise AI ecosystem. You will also collaborate with the

Primary Research Lead to apply AI and advanced analytics techniques in high-impact research programs on critical business topics to uncover novel insights that support publication of thought leadership on EY.com. In this role, you will operate as a

player–coach , leading the most complex initiatives while building and mentoring a

high-performing, multidisciplinary team of data scientists, data engineers, and visualization specialists. Partnering with analysts, business stakeholders, and technology teams across EY, you will translate strategic priorities into scalable, trusted AI products that leverage enterprise infrastructure, align with governance standards, and integrate cleanly into EY’s evolving AI platform.

Key Responsibilities AI and Analytics Strategy

• Shape the long-term AI and analytics strategy for EY Insights in partnership with Global Insights leadership.
• Identify opportunities to leverage LLMs, AI agents, and agentic workflows to enhance efficiency, insight generation and knowledge discovery.
• Define how EY Insights products integrate with EY’s enterprise AI platforms

AI Product Development & Delivery

• Own delivery and lifecycle management of a portfolio of AI and analytics products, including product roadmap, prioritization, and release cadence.
• Lead and oversee the development of predictive models, machine learning pipelines, and LLM-enabled applications that generate differentiated insights.
• Partner with senior analysts and business stakeholders to translate strategic priorities into new, scalable products and solutions.

MLOps, Data Platforms & Engineering Excellence

• Define and implement MLOps standards for model development, deployment, monitoring, and lifecycle management.
• Ensure AI solutions leverage Azure data platforms, modern data engineering pipelines, and scalable cloud infrastructure.
• Build strong relationships with technology and governance teams to ensure alignment with enterprise platforms, standards and responsible AI principles.

Market Research and Insight development

• In collaboration with the Primary Research Lead, identify opportunities to apply data science and statistical methods to uncover deeper insights as part of mixed-methods research programs on critical business issues.
• Advise on appropriate analytical techniques, leading or overseeing modelling and analysis to ensure analysis is rigorous and aligned to research objectives.
• Support interpretation of findings for a general business audience, helping translate analytical results into insights that support the broader research narrative.

Team Leadership & Capability Building

• Lead and grow the AI and Applied Analytics team, including defining team structure, hiring priorities, and technical mentorship.
• Operate as a player–coach, contributing hands-on to complex initiatives while guiding delivery across data science, data engineering, and visualization teams.
• Establish best practices for AI engineering and production delivery, including Git-based workflows, code reviews, CI/CD pipelines, and documentation standards.
• Foster a culture of innovation, experimentation, and continuous learning

Skills And Attributes For Success

• Deep expertise in AI, machine learning, and applied analytics, with experience delivering production-grade AI solutions.
• Proven experience building multidisciplinary teams spanning data science, data engineering, and analytics.
• Strong experience building and scaling AI and analytics products and platforms in enterprise environments.
• Hands-on experience with MLOps practices, including model lifecycle management, automated pipelines, and monitoring.
• Experience building or deploying LLM-enabled solutions, such as retrieval-augmented generation (RAG), AI agents, or generative AI applications.
• Strong understanding of modern cloud AI ecosystems, particularly Microsoft Azure, Azure AI services, Azure ML, and Databricks.
• Experience working with data engineering platforms and scalable data architectures.
• Proficiency with modern development workflows including GitHub-based collaboration, CI/CD pipelines, and infrastructure automation.
• Strong expertise in predictive modelling, statistical analysis, and machine learning methods including regression, time series, network analysis, and advanced ML algorithms.
• Executive communication and stakeholder management skills, with the ability to explain complex technical concepts to non-technical audiences.
• Experience applying data science methods to analyse quantitative and qualitative data sets in a market research or academic setting is a plus

What We Look For

• Experience building multi-disciplinary teams and establishing reliable, scalable foundations for AI and analytics products
• A strong ownership mindset with demonstrated ability to drive complex initiatives from concept to production.
• Passion for building scalable, enterprise AI and analytics capabilities
• Curiosity to explore and experiment with emerging technologies
• Ability to operate effectively in a complex, global organization with multiple stakeholders.

What We Offer

• The opportunity to shape and lead a growing Applied AI and Analytics capability within EY Insights.
• Direct exposure to senior leadership and the chance to influence high-impact insight products with global commercial relevance.
• A collaborative, multidisciplinary team environment focused on innovation, experimentation, and continuous learning.
• Access to modern enterprise AI, data, and cloud platforms, with the mandate to help define how they are used and scaled across EY.

EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.