AI, GenAI & RPA Analyst (MedTech, Healthcare, or Life Sciences)

Role: AI, GenAI & RPA Analyst (MedTech, Healthcare, or Life Sciences)Duration: Long Term Contract (C2C)Location: Minneapolis, MN (Onsite) Role OverviewThis is a strategic Business Analyst role focused on scaling hyperautomation and AI-driven transformation within global MedTech operations. The candidate will identify, analyze, and deliver high-impact automation use cases using AI, GenAI, RPA, and Data Analytics, ensuring a structured roadmap, actionable business cases, and measurable ROI.Must-Have Qualifications8+ years in business analysis, process improvement, or automation within large organizations.2-3 years in MedTech, Healthcare, or Life Sciences with experience in AI, Data, and Automation programs.Proven expertise in use case diagrams, PDDs, BRDs, workshops, ROI analysis, and automation roadmaps.Hands-on experience across AI, Data, RPA, and GenAI (not just one area).Key ResponsibilitiesUse Case Identification & Prioritization – Collaborate with IT, Finance, HR, and MedTech teams to evaluate automation opportunities.Business Process Analysis – Lead process mining initiatives to identify inefficiencies and automation points.Automation Strategy & Roadmap – Develop short- and long-term automation roadmaps aligned with business goals.Stakeholder Engagement – Secure leadership sponsorship through compelling business cases.Solution Design & Documentation – Define automation requirements and ensure regulatory compliance.ROI & Impact Analysis – Design ROI simulations and track post-implementation outcomes.Workshops & POV Development – Organize automation idea sessions and showcase AI/RPA capabilities.Risk Management – Ensure compliance with MedTech industry regulations (FDA, ISO, GMP).Key Skills & ExpertiseMedTech Industry Knowledge – Strong understanding of regulatory compliance and operations.Process Automation Frameworks – Expertise in Lean, Six Sigma, Agile, ITIL.Automation & Analytics Tools – Experience with UiPath, Automation Anywhere, Blue Prism, AI/ML frameworks.Business Documentation – Proficiency in BRDs, PDDs, ROI models, and functional architecture.Data-Driven Decision Making – Conduct EDA and ‘What If’ analyses to drive automation insights.