Associate AI Business Analyst

Associate AI Business Analyst

Full-time/Permanent

Location:

NYC – Must be local and onsite 4-5 days a week

No 3rd parties/sponsorship

Co-Lead Stakeholder

Collaboration:

• In partnership with the AVP on the team, you will partner with business stakeholders and IT teams to identify, qualify, and prioritize AI opportunities that enhance decision-making, accuracy, and efficiency.
• Facilitate workshops, structured interviews, and working sessions with bankers and support functions to understand workflows, pain points, and desired outcomes.
• Act as a trusted bridge between technical teams and business users, ensuring clear communication and alignment throughout the project lifecycle.
• Present findings, recommendations, and project updates to cross-functional teams and management, tailoring message and detail to the audience.

• Own the end-to-end requirements process for assigned AI initiatives, from discovery through sign-off.
• Document and refine business requirements, user stories, and acceptance criteria for AI-driven solutions.
• Create and maintain artifacts such as process maps, swim lane diagrams, data flow diagrams, and use-case briefs.
• Translate complex business needs into actionable technical deliverables for engineering and data science teams and support backlog prioritization in Agile ceremonies where applicable.

• Analyze existing business processes and data flows to identify bottlenecks, manual work, and automation opportunities.
• Design workflows and process flows that align business use cases with AI capabilities (e.g., generative AI assistants, intelligent document processing, AI agents).
• Collaborate with data scientists and engineers to prototype, test, and deploy AI solutions, providing structured feedback and ensuring business requirements are met.
• Coordinate and support user acceptance testing (UAT), including test case definition, execution tracking, and defect triage.
• Ensure solutions are scalable, secure, and aligned with organizational goals, controls, and standards.

• Define and track KPIs and success metrics for AI use cases (e.g., time saved, accuracy improvements, revenue enablement, error reduction).
• Analyze usage patterns, performance metrics, and business outcomes from deployed AI tools; synthesize insights into clear recommendations.
• Support documentation related to model behavior, data lineage, controls, and explainability in partnership with risk, legal, and compliance teams.

• Research emerging AI technologies and platforms, especially generative AI, large language models, and workflow automation tools, and assess their applicability to investment banking workflows.
• Benchmark company's initiatives against external market trends and best practices in AI for financial services.
• Contribute to internal best practices, playbooks, and templates for AI business analysis.
• Help develop training materials, demos, and change management plans to drive adoption and AI literacy across the firm.

• Bachelor's Degree required, with preferred emphasis in Information Systems, Data Science/Analytics, Computer Science, Finance or related field.
• 2 – 4 years of experience as a Business Analyst or similar role.
• Experience with in financial services industry is preferred, however, candidates from all backgrounds will be considered.
• Excellent communication and stakeholder management abilities; able to influence, synthesize input from multiple parties, and drive alignment.
• Strong analytical and problem-solving skills; able to turn qualitative and quantitative data into clear insights and action.
• Advanced skills in Microsoft Excel, PowerPoint, and Word, including building structured analyses and executive-ready presentations.

• Experience working with Python (and ideally SQL or data analytics tools such as Power BI or Tableau) to explore data, run analyses, or prototype solutions.
• Familiarity with generative AI tools, large language models, or automation platforms (e.g., ChatGPT, Copilot, Gemini, Power Automate, UiPath) and an understanding of how they can be embedded in business workflows.
• Understanding of core software delivery concepts (e.g., Agile, backlog management, UAT, release planning).