Senior AI Analyst

Overview

Senior Associate role in the Strategy, Insights & Performance team at LSEG, supporting the Research Insights & Analytics (RIA) group in shaping and delivering AI-enabled use cases.

What you'll do

• Work with teams across RIA to shape and deliver AI-enabled use cases, from early ideas through to adoption.
• Collaborate with business partners to explore opportunities where AI can support efficiency, insight generation, and decision-making.
• Contribute to the evaluation and use of tools, methods, and approaches aligned with LSEG-approved AI and analytics platforms.
• Support the development of AI solutions that align with LSEG governance, risk, and compliance requirements.
• Help embed AI-driven insights into existing delivery channels, such as dashboards, reports, workflows, and client outputs.
• Support adoption by contributing to documentation, knowledge-sharing sessions, and practical guidance for RIA users.
• Share perspectives on how AI insights can be applied within everyday workflows and decision-making.

What you'll need

• Experience working with AI-enabled or data-driven solutions, including exposure to large language models (LLMs), in a business or enterprise environment.
• Experience supporting projects or initiatives that involve multiple teams, priorities, or stakeholders.
• Ability to help shape and structure business questions into AI-, LLM-, or analytics-based use cases.
• Experience using or supporting enterprise tools and platforms, such as approved AI, LLM, analytics, data, or reporting solutions.
• Clear communication skills, with the ability to explain AI and LLM-related concepts in accessible ways to a wide range of audiences.

Nice to have

• Experience working in financial services, data, research, or information-focused environments.
• Awareness of topics such as AI governance, model risk, and responsible AI, with interest in applying these principles in practice.
• Experience using applied analytics or data science approaches, with exposure to tools such as Python, R, or SQL.
• Experience working with large or complex datasets in a business setting.
• Experience contributing insights to operational processes or client-facing outputs.
• Exposure to change, enablement, or adoption-focused activities.
• An organised approach to work, with attention to detail and an ability to manage priorities.
• Curiosity and a proactive approach to learning and continuous improvement.
• A collaborative, stakeholder-focused mindset, with the ability to work effectively with others.
• A practical approach, with interest in delivering meaningful business outcomes.