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Accenture

Advises businesses and runs their technology

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

Strategy & Management ConsultingConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A 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.
  • A minimum of 6 years of experience in life sciences commercial transformation, commercial strategy, operating models, or AI/data strategy.
  • A minimum of 5 years of experience in strategy consulting, professional services, or an equivalent internal corporate-strategy role.
  • A 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.
  • Working knowledge of how different AI/model types work and where they are best applied, including predictive analytics, generative AI, 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 applying AI/data responsibly in commercial workflows, including its value, risks and dependencies, 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.
  • Comfort partnering with technology, analytics, AI, and platform teams while staying anchored in the business problem.
  • Problem-solving, storytelling, PowerPoint, Excel, facilitation, and executive communication skills.

Responsibilities

  • Lead client workstreams that translate commercial ambition 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 where AI, analytics, automation, copilots, or agentic workflows can create measurable value through improvements to speed, scale, quality, decision-making, productivity, customer engagement, or ways of working.
  • Frame AI/data approaches for priority use cases, including data inputs, workflow integration, human-in-the-loop controls, governance considerations, and value measurement.
  • Assess current-state processes, handoffs, governance, data flows, technology dependencies, and value leakage points.
  • Build 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; 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 and 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.
  • Identify value opportunities where commercial transformation and AI/data-enabled ways of working can drive growth, efficiency, quality, decision speed, customer impact, or better patient outcomes.
  • Define value drivers, KPI measures, baseline assumptions, adoption metrics, and tracking mechanisms to determine whether value is being realized in practice.
  • Use data-driven storytelling to connect 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.
  • Guide clients in selecting suitable approaches—including rules-based automation, predictive models, generative AI, copilots, and agents—based on use case, data readiness, workflow complexity, risk, and required human oversight.
  • Guide clients through practical decisions about AI/data use cases, model limitations, agent design considerations, dependencies, and adoption risks.
  • Support proactive commercial reinvention opportunities and 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.

Desired Qualifications

  • Ability to lead a workstream, manage clients, and coach junior team members.
  • Client management skills, including building trusted relationships, facilitating working sessions, managing feedback, aligning stakeholders, and clearly communicating risks and tradeoffs.
  • Ability to translate AI/data concepts into practical business use cases, transformation roadmaps, and measurable value opportunities.
  • Proactive approach to innovative ways of working, including applying AI, automation, copilots, and agentic workflows to improve productivity, quality, collaboration, and speed of execution for external projects and internal Accenture work.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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