Business Analyst

Why this role matters AI products only succeed when they solve the right problem in a way people can trust. As our Business Analyst, you’ll be the bridge between business intent and what gets built, turning ambiguous needs into clear, testable requirements and keeping stakeholders, backlog, and validation aligned from first workshop through UAT sign-off. Experience: 4 to 8 years in business analysis, including at least 2 years delivering data, analytics, or AI/ML products. What you’ll do Lead discovery workshops to uncover how work happens today, where it breaks, who the users are, and which use cases matter most Write BRDs, FRDs, user stories, and acceptance criteria that engineers can build from and testers can verify Partner with the Product Owner to refine and prioritize the backlog by business value and data readiness Map end-to-end workflows, including intake, review, approval, and escalation across functions Work with subject matter experts to define business rules, thresholds, scoring logic, severity levels, and KPIs Run configuration sessions and translate decisions into precise build specifications Maintain traceability from requirements through build, testing, and delivery Plan and drive UAT: test scenarios, business validation of AI outputs, defect triage, and sign-off Contribute to RAID and decision logs, status reporting, and change-control assessments Create user playbooks, process documentation, and handover materials What you bring Strong requirements elicitation, process modeling (BPMN or similar), and gap analysis Agile delivery experience with Jira, Azure DevOps, or similar, in two-week sprints Working SQL and data literacy, enough to read schemas, metadata, and data profiles to validate requirements The ability to define acceptance criteria for AI features, covering accuracy, confidence, and evidence Clear communication with business, technical, and executive audiences Confident workshop facilitation that brings multiple stakeholders to one agreed requirement set Bonus points for Experience with GenAI, LLM, RAG, or agentic AI products, including human-in-the-loop design Familiarity with data governance: metadata, catalogs, taxonomies, quality rules, and lineage Pharma or life sciences domain knowledge (commercial, medical, regulatory, launch, or content review) Experience defining requirements for Power BI or Tableau dashboards CBAP, CCBA, PMI-PBA, or CSPO certification