Life Sciences Manager — Commercial Strategy & Transformation, Data​/AI

Overview​Join our Life Sciences Industry & Enterprise practice to help leading pharma, biotech, and medtech clients reinvent how commercial work gets done. This role focuses on commercial transformation across field, marketing, market access, patient services, medical, and commercial operations, with AI/data fluency as a core enabler of future ways of working and measurable value creation.​​What would you do?​As a Manager, you will lead client work streams that translate commercial ambition into future-state operating models, redesigned workflows, governance, capabilities, and AI/data-enabled transformation roadmaps.​Your

work could include:​Redesigning commercial operating models across field, marketing, access, patient services, medical, and commercial operations​Identifying where AI, analytics, automation, copilots, or agentic workflows can unlock measurable value by improving speed, scale, quality, decision-making, productivity, customer engagement, or ways of working​Framing the right AI/data approach for priority use cases, including required data inputs, workflow integration, human-in-the-loop controls, governance considerations, and value measurement​Assessing current-state processes, handoffs, governance, data flows, technology dependencies, and value leakage points​Building future-state workflows, capability models, business cases, value cases, and transformation roadmaps​Facilitating cross-functional design sessions with business, technology, analytics, and operations stakeholders​In this role you will be expected to:​Anticipate risks, dependencies, and shifting client priorities;

prepare teams to pivot as programs evolve while keeping delivery focused on outcomes​Shape ambiguous client objectives into clear workplans, hypotheses, analyses, and deliverables​Lead work streams and manage analysts/consultants to produce client-ready outputs​Manage day-to-day client relationships, including working sessions, feedback, risks, and next steps​Apply life sciences commercial knowledge to connect strategy, operating model, process, data, technology, and talent implications​Define value unlock opportunities by identifying where commercial transformation and AI/data-enabled ways of working can drive growth, efficiency, quality, decision speed, customer impact, or better patient outcomes​Translate value opportunities into measurable outcomes by defining value drivers, KPIs, baseline assumptions, adoption metrics, and tracking mechanisms to understand whether value is being realized in practice​Use data-driven storytelling to link transformation recommendations, AI/data use cases, and future ways of working to measurable business value​Prioritize AI/data use cases based on value potential, feasibility, adoption risk, workflow fit, governance needs, and ability to measure impact​Understand how different AI / analytics approaches create value — including rules-based automation, predictive models, GenAI, copilots, and agents — and guide clients on when each is appropriate based on use case, data readiness, workflow complexity, risk, and required human oversight​Possess a cutting-edge perspective on AI/data use cases, model limitations, agent design considerations, dependencies, and adoption risks;

and guide clients through practical decision-making with those considerations in mind​Support proactive commercial reinvention opportunities and proposals by shaping the client problem, strategic approach, workplan, and value story​Contribute to thought capital by developing reusable perspectives, frameworks, case examples, and market-facing points of view on AI/data-enabled commercial transformation and future ways of working

Growth Opportunities​You will continue to grow through:​Leading…