- Company Name
- emagine
- Job Title
- Business Analyst - Generative AI (Banking/AML)
- Job Description
-
**Job Title**
Business Analyst – Generative AI (Banking/AML)
**Role Summary**
Lead the definition, documentation, and delivery of Generative AI solutions within banking operations. Act as a bridge between business stakeholders, data professionals, and technology teams to transform complex operational challenges into AI‑enabled use cases that enhance compliance, risk, and operational efficiency.
**Expectations**
- Collaborate with AML, Legal, Operations, Risk, and Technology stakeholders to capture strategic objectives.
- Translate business problems into clear GenAI requirements and use cases.
- Ensure alignment with regulatory standards, AI governance, and the bank’s AI roadmap.
- Contribute to the establishment of best‑practice frameworks for AI delivery within a scaling team.
**Key Responsibilities**
- Elicit, analyze, and document business and functional requirements for GenAI initiatives.
- Translate high‑level business challenges into actionable AI use cases.
- Analyze unstructured data (legal texts, documents, narratives) to support model development.
- Conduct gap analysis, process mapping, and workflow assessment to identify automation opportunities.
- Coordinate with data scientists, AI engineers, architects, and IT teams to validate requirements.
- Organize data preparation activities for model training and testing.
- Define acceptance criteria, success metrics, and performance thresholds for model evaluation.
- Lead discussions on model explainability, risk, and business implications.
- Develop end‑to‑end test strategies and support UAT with subject‑matter experts.
- Validate GenAI outputs against business expectations, regulatory constraints, and operational needs.
- Contribute to templates, frameworks, and best‑practice documentation for AI projects.
**Required Skills**
- Proven Business Analyst experience in banking or financial services.
- Deep knowledge of Generative AI concepts and practical application to business problems.
- Ability to translate complex business requirements into structured documentation and technical specs.
- Strong analytical and problem‑solving skills, particularly with unstructured or text‑based data.
- Excellent cross‑functional communication; simplify technical concepts for non‑technical stakeholders.
- Agile experience (Scrum, Kanban, scaled Agile).
- Adaptability to fast‑evolving environments and ability to build new processes and frameworks.
**Nice‑to‑Have Skills**
- AML regulation knowledge and experience in finance‑crime or compliance projects.
- Familiarity with AI/ML or data analysis tools (Python basics, SQL, NLP tooling, annotation platforms).
- Exposure to project management tools (Jira, Confluence, MS Project, Smartsheet).
- Experience collaborating with Legal, Risk, or Controls teams on documentation‑heavy workflows.
**Required Education & Certifications**
- Bachelor’s degree in Business, Finance, Computer Science, or related field.
- Professional certifications (e.g., CBAP, PMI‑PBA, Agile certifications) are advantageous but not mandatory.