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

Accenture•Miami, FL

3d•$87,400 - $253,000

About The Position

The Life Sciences Manager will join Accenture’s Life Sciences Industry & Enterprise practice, helping pharmaceutical, biotechnology, and medical technology clients transform commercial work across field, marketing, market access, patient services, medical, and commercial operations. The role focuses on commercial strategy and transformation, with data and AI fluency supporting future ways of working and measurable value creation. The Manager leads client workstreams to turn commercial ambitions into future-state operating models, redesigned workflows, governance, capabilities, and AI/data-enabled transformation roadmaps. This includes assessing processes, handoffs, governance, data flows, technology dependencies, and value leakage; developing workflows, capability models, business and value cases, and roadmaps; and facilitating cross-functional design sessions with business, technology, analytics, and operations stakeholders. The role also identifies, prioritizes, and shapes AI and data use cases, considering value potential, feasibility, adoption risk, workflow fit, governance, data readiness, human oversight, and impact measurement. The Manager translates opportunities into measurable outcomes through value drivers, KPIs, baseline assumptions, adoption metrics, and tracking mechanisms. They manage client relationships and delivery teams, shape proposals and thought capital, and partner across Accenture to deliver integrated strategy, technology, analytics, and operations solutions. Accenture is a global professional services company with approximately 791,000 people serving clients in more than 120 countries. The posted annual salary range is $87,400 to $253,000 in the listed U.S. locations. The posting is anticipated to remain open until 10/06/2026.

Requirements

At least 6 years of life sciences commercial experience across one or more of field, marketing, market access, patient services, medical, or commercial operations.
At least 6 years of experience in life sciences commercial transformation, commercial strategy, operating models, or AI/data strategy.
At least 5 years of experience in strategy consulting, professional services, or an equivalent internal corporate-strategy role.
Bachelor’s degree.
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.
Strong problem-solving, storytelling, PowerPoint, Excel, facilitation, and executive communication skills.

Nice To Haves

Ability to lead a workstream, manage clients, and coach junior team members.
Strong client management skills, including building trusted relationships, facilitating working sessions, managing feedback, aligning stakeholders, and clearly communicating risks and tradeoffs.
Working knowledge of predictive analytics, GenAI, copilots, workflow automation, and agentic solutions, including how different AI/model types work and where they are best applied.
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 approaches, and measurement criteria.
Practical understanding of responsible AI/data applications in commercial workflows, associated risks and dependencies, and 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 perspective on using AI, automation, copilots, and agentic workflows to improve productivity, quality, collaboration, and speed in client and internal work.
Comfort partnering with technology, analytics, AI, and platform teams while staying anchored in the business problem.

Responsibilities

Lead client workstreams to translate commercial ambitions into future-state operating models, redesigned workflows, governance, capabilities, and AI/data-enabled transformation roadmaps.
Redesign commercial operating models across field, marketing, market access, patient services, medical, and commercial operations.
Identify and prioritize AI, analytics, automation, copilot, and agentic workflow opportunities based on value, feasibility, workflow fit, adoption risk, governance, and measurability.
Frame AI/data approaches for priority use cases, including data inputs, workflow integration, human-in-the-loop controls, governance, and value measurement.
Assess current-state processes, handoffs, governance, data flows, technology dependencies, and value leakage points.
Develop future-state workflows, capability models, business cases, value cases, and transformation roadmaps.
Facilitate cross-functional design sessions with business, technology, analytics, and operations stakeholders.
Anticipate risks, dependencies, and changing client priorities, and prepare teams to adapt while maintaining outcome-focused delivery.
Shape ambiguous client objectives into clear workplans, hypotheses, analyses, and deliverables.
Lead workstreams and manage analysts and consultants to produce client-ready outputs.
Manage day-to-day client relationships, working sessions, feedback, risks, and next steps.
Apply life sciences commercial knowledge to connect strategy, operating model, process, data, technology, and talent implications.
Identify value opportunities and define measurable outcomes using value drivers, KPIs, baseline assumptions, adoption metrics, and tracking mechanisms.
Use data-driven storytelling to connect recommendations, AI/data use cases, and future ways of working to measurable business value.
Guide clients on appropriate AI and analytics approaches, including rules-based automation, predictive models, GenAI, copilots, and agents, considering use case, data readiness, workflow complexity, risk, and human oversight.
Guide practical client decisions using knowledge of AI/data use cases, model limitations, agent design considerations, dependencies, and adoption risks.
Support commercial reinvention proposals by shaping the client problem, strategic approach, workplan, and value story.
Develop reusable perspectives, frameworks, case examples, and market-facing points of view on AI/data-enabled commercial transformation and future ways of working.
Partner across Accenture to deliver integrated strategy, technology, analytics, and operations solutions.