**_This position follows our hybrid-friendly schedule, so you get the best of both worlds – flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office._** **Summary:** As part of our Wealth Management Technology Team, Lead Analyst will serve as a strategic partner to business and IT teams, driving the delivery of innovative, scalable, and efficient technology solutions. You will lead the end-to-end analysis process, from requirements gathering and documentation to solution validation and implementation support. This role requires a blend of business acumen, technical expertise, and leadership to influence outcomes and ensure alignment with organizational goals. **Responsibilities:** + Lead the elicitation, documentation, and management of business and functional requirements for complex technology initiatives. + Translate business needs into clear, actionable technical requirements and user stories. + Conduct gap analyses, feasibility studies, and impact assessments to support solution design and decision-making. + Collaborate with cross-functional teams including developers, QA, UX, and business stakeholders to ensure successful delivery. + Facilitate user acceptance testing (UAT), validate test cases, and ensure solutions meet business expectations. + Create and maintain process flows, wireframes, prototypes, and technical/user documentation. + Act as a subject matter expert (SME) for assigned systems and business domains. + Support production issue triage and resolution, including after-hours support on a rotational basis. + Apply risk management, change control, and issue tracking best practices throughout the project lifecycle. + Use AI assisted requirements analysis to refine BRDs, functional specs, workflow documents, and process gaps with clarity and consistency. + Apply prompt engineering techniques to improve the quality of BRDs, UI mockups, user stories, acceptance criteria, and test cases. + Partner with product owners to generate AI drafted user stories, refine them, and ensure they are aligned with business goals + Use AI tools (e.g., Copilot Chat, M365 Copilot) to break down business requirements into structured, detailed acceptance criteria and ready for development artifacts. + Leverage AI to generate test scenarios, edge cases, and validation steps, ensuring full coverage and reducing missed requirements. + Use AI to quickly produce process maps, workflow diagrams, UI mockups and impact assessments, validating accuracy through stakeholder sessions. + Support engineering teams by providing AI generated documentation drafts (API descriptions, data mappings, field definitions) that can be refined collaboratively. + Maintain a library of high quality prompts for business analysis activities—BRD drafting, story writing, test case expansion, root cause investigation, and documentation. + Use AI to accelerate competitive analysis, research, and data gathering, summarizing findings and synthesizing insights for leadership. **Skills:** + 6–10 years of experience in business analysis, required in financial services or enterprise technology environments. + Strong understanding of SDLC, Agile, Waterfall, and hybrid methodologies. + Proficiency in SQL and data analysis; experience with tools like TFS, Azure DevOps, ServiceNow, Splunk and Postman. + Experience with wireframing and prototyping tools (e.g., Visio, Marvel). + Demonstrated ability to manage multiple priorities and switch between projects as needed. + Excellent communication skills with the ability to translate between technical and business audiences. + Proven ability to influence stakeholders and drive consensus across diverse teams. + Experience with vendor-based software implementations and enterprise-level applications is a plus. + Demonstrated experience using AI tools for business analysis, including BRD drafting, story reformulation, process analysis, and test case generation. + Strong prompt engineering capability: ability to design structured prompts, iterate for accuracy, and validate results against business intent. + Ability to evaluate AI generated requirements, flows, and test cases with a critical eye—ensuring completeness, correctness, and alignment with regulatory needs. + Hands on experience with tools such as M365 Copilot, GitHub Copilot Chat, Azure OpenAI Chat, or equivalent AI assistants. + Strong understanding of responsible AI usage: safeguarding client data, avoiding PII in prompts, and adhering to company compliance standards. + Skill in refining AI generated artifacts into developer ready, test ready, and stakeholder approved deliverables.