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

About the role

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.

As a Manager, you will lead client workstreams that translate commercial ambition into future-state operating models, redesigned workflows, governance, capabilities, and AI/data-enabled transformation roadmaps.

Responsibilities

• 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
• Anticipating risks, dependencies, and shifting client priorities; preparing teams to pivot as programs evolve while keeping delivery focused on outcomes
• Shaping ambiguous client objectives into clear workplans, hypotheses, analyses, and deliverables
• Leading workstreams and managing analysts/consultants to produce client-ready outputs
• Managing day-to-day client relationships, including working sessions, feedback, risks, and next steps
• Applying life sciences commercial knowledge to connect strategy, operating model, process, data, technology, and talent implications
• Defining 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
• Translating 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
• Using data-driven storytelling to link transformation recommendations, AI/data use cases, and future ways of working to measurable business value
• Prioritizing AI/data use cases based on value potential, feasibility, adoption risk, workflow fit, governance needs, and ability to measure impact
• Understanding how different AI/analytics approaches create value—including rules-based automation, predictive models, GenAI, copilots, and agents—and guiding clients on when each is appropriate based on use case, data readiness, workflow complexity, risk, and required human oversight
• Possessing a cutting-edge perspective on AI/data use cases, model limitations, agent design considerations, dependencies, and adoption risks; and guiding clients through practical decision-making with those considerations in mind
• Supporting proactive commercial reinvention opportunities and proposals by shaping the client problem, strategic approach, workplan, and value story
• Contributing 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

• Leading enterprise commercial reinvention work for major life sciences clients
• Building expertise at the intersection of commercial strategy, operating model, AI/data, transformation, and value realization
• Developing expertise in how AI/data-enabled commercial transformation creates value, how value is measured, and how adoption translates into sustained business impact
• Partnering across Accenture to deliver integrated strategy, technology, analytics, and operations solutions
• Developing market-facing perspectives on AI-enabled commercial reinvention and future ways of working

Requirements

• Minimum of 6 years of life sciences commercial experience across one or more commercial functions: field, marketing, market access, patient services, medical, or commercial operations
• Minimum of 6 years of life sciences commercial transformation, commercial strategy, operating model, or AI/data strategy experience
• Minimum of 5 years of experience in strategy consulting, professional services, or an equivalent internal corporate-strategy role
• Bachelor's Degree

Qualifications

• Demonstrated ability to lead a workstream, manage clients, and coach junior team members
• Strong client management skills, including ability to build trusted relationships, facilitate working sessions, manage feedback, align stakeholders, and communicate risks/tradeoffs clearly
• Strong understanding of commercial workflows, cross-functional handoffs, governance, and capability needs
• Ability to translate AI/data concepts into practical business use cases, transformation roadmaps, and measurable value opportunities
• Working knowledge of how different AI/model types work and where they are best applied, including predictive analytics, GenAI, copilots, workflow automation, and agentic solutions
• Experience designing or shaping AI-enabled workflows or agents, including defining use case objectives, input/output requirements, data and system dependencies, decision rights, orchestration logic, guardrails, testing approach, and measurement criteria
• Practical understanding of how AI/data can be applied responsibly in commercial workflows, including where it creates value, what risks or dependencies must be managed, and how to support adoption with appropriate human oversight
• Experience building future-state operating models, process maps, capability models, governance models, business cases, value cases, or implementation plans
• Proactive mindset around innovative ways of working, including how AI, automation, copilots, and agentic workflows can improve productivity, quality, collaboration, and speed of execution for external project and internal Accenture work
• Comfort partnering with technology, analytics, AI, and platform teams while staying anchored in the business problem
• Strong problem-solving, storytelling, PowerPoint, Excel, facilitation, and executive communication skills

Pay

Compensation at Accenture varies depending on location, role, skill set, and level of experience. The following ranges are provided as required by local law:

• California: $87,400 to $253,000
• Cleveland: $87,400 to $253,000
• Colorado: $87,400 to $253,000
• District of Columbia: $87,400 to $253,000
• Illinois: $87,400 to $253,000
• Maine: $87,400 to $253,000
• Maryland: $87,400 to $253,000
• Massachusetts: $87,400 to $253,000
• Minnesota: $87,400 to $253,000
• New York: $87,400 to $253,000
• New Jersey: $87,400 to $253,000
• Virginia: $87,400 to $253,000
• Washington: $87,400 to $253,000

Benefits

Accenture offers a market-competitive suite of benefits including:

• Medical, dental, vision, life, and long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off

See more information on our benefits here.