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

Accenture•St. Louis, MO

1d•$87,400 - $253,000•Hybrid

About The Position

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.

Requirements

Minimum of 6 years of life sciences commercial cross one or more commercial functions: field, marketing, market access, patient services, medical, or commercial operations
Minimum of 6 years 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

Nice To Haves

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

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
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 workstreams 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