Data Analyst (AI)

Location: London, England, United Kingdom; hybrid work arrangement

Base salary: £55,000–£70,000 per year.

Company

Connor, Clark & Lunn Financial Group is an investment organization developing technology-enabled research and decision-support solutions.

What you will do

• Develop investment data strategies that improve the accessibility, quality, and usability of research and portfolio information.
• Build and maintain data pipelines, databases, and data models integrating Microsoft Fabric, SharePoint, and internal systems.
• Use Python, SQL, and modern data engineering tools to automate data processing, analytics, and workflows.
• Integrate portfolio, trading, performance, and research data with data, technology, and AI engineering teams.
• Design AI-powered access to research, meeting notes, and decision-making history using LLMs, RAG, semantic search, document processing, and AI agents.
• Prototype, test, and refine dashboards, applications, and user tools, then transition successful solutions into scalable production applications in partnership with investment professionals.

Requirements

• Builder mindset with experience rapidly developing, testing, and iterating practical solutions.
• Strong Python and SQL programming skills with experience in application development, automation, or data-focused projects.
• Passion for AI technologies, including LLMs, AI agents, and AI-powered application development.
• Experience with Microsoft data and analytics platforms such as Microsoft Fabric, Azure, and Power BI.
• Knowledge of SharePoint, Microsoft Graph, Microsoft 365 integrations, and enterprise data ecosystems.
• Understanding of data engineering concepts including ETL pipelines, database design, APIs, cloud services, and application development.
• Familiarity with LLM APIs, RAG architectures, vector databases, and agent frameworks.
• Experience with software development best practices, Git, testing, AI coding assistants, collaboration, and continuous learning.
• Strong problem-solving skills, willingness to learn unfamiliar technologies, self-motivation, and ability to work independently with minimal supervision.

Culture & Benefits

• Collaborative, inclusive, entrepreneurial environment with flexibility in where and how work is performed.
• Social events, volunteering opportunities, and support for corporate social responsibility.
• Continuous learning budgets, paid study days, and support for professional designations.
• Competitive total compensation, retirement savings support, wellness credits, enhanced parental leave, and comprehensive health benefits.
• Inclusive and accessible recruitment and selection process, with accommodations available on request.
• AI may support certain screening and recruitment stages without replacing human judgment.