Business Analyst - Generative AI; Banking​/AML; h​/f

Responsibilities

• Work closely with business stakeholders across AML, Legal, Operations, Risk, and Technology to understand business challenges and strategic objectives.
• Define, document, and prioritise clear business and functional requirements for GenAI and AI-enhanced solutions.
• Translate complex operational problems into GenAI-enabled use cases, ensuring alignment with business value and feasibility.
• Analyse unstructured data, including legal texts, documents, and narrative fields, to support GenAI model development.
• Conduct gap analysis, process mapping, and workflow assessment to identify automation and optimisation opportunities.
• Collaborate with data scientists, AI engineers, architects, and IT teams to ensure requirements are accurately understood and implemented.
• Organise, validate, and collate data inputs required for model training and testing activities.
• Support model evaluation by helping define acceptance criteria, success metrics, and performance thresholds.
• Facilitate discussions on model explainability, risk considerations, and business implications.
• Ensure alignment of project outcomes with the bank's broader AI strategy, governance standards, and adoption roadmap.
• Contribute to establishing best practices, templates, and frameworks for AI delivery within a scaling team.
• Define end-to-end test strategies for AI features and workflows.
• Coordinate and support User Acceptance Testing (UAT) with business SMEs.
• Validate outputs from GenAI models against business expectations, regulatory considerations, and operational constraints.

• Proven experience as a Business Analyst within banking or financial services.
• Strong working knowledge of Generative AI concepts, capabilities, and methodologies, with practical experience applying AI solutions to business problems.
• Demonstrable ability to translate complex business requirements into clear, structured documentation and technical specifications.
• Strong analytical and problem‑solving skills with experience handling unstructured or text‑based data.
• Effective communication skills for engaging cross‑functional teams and simplifying technical concepts for non‑technical stakeholders.
• Experience working within Agile environments (Scrum, Kanban, scaled Agile).
• Ability to work in fast‑evolving environments and contribute to building new processes and frameworks.

• Familiarity with AI/ML or data analysis tools (eg, Python basics, SQL, NLP tooling, annotation platforms).
• Exposure to project management practices and tools (Jira, Confluence, MS Project, Smartsheet, etc.).
• Experience working with Legal, Risk, or Controls teams on documentation‑heavy workflows.

emagine is a high‑end professional services consultancy and solutions firm Specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high‑end consulting services and solutions.

We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication in delivering the optimal service for our clients. Our commitment is not just towards our clients but we aim to foster a positive and equitable working environment with our consultants and colleagues which stems from our core values:
Confident, Dedicated, Responsible, Genuine.

The role will be working within our Technology Change practice where we are partnered on Generative AI (GenAI) projects across multiple business units as part of a strategic roadmap. To support this journey, we are seeking a Business Analyst with strong GenAI expertise who can operate at the intersection of business operations, data, and emerging technology. This consultant will be instrumental in enabling the build and scale of Generative AI capability from the ground up.

With the AI team still in early growth stages, this is a unique opportunity to shape strategic direction, establish foundational ways of working, and deliver meaningful AI‑enabled improvements across different operations.