Life Sciences AI Planning Transformation Leader

Accenture; Culver City (CA); On-site; USD 133,000 - 338,000; Full time

Job summary

Accenture is seeking a Senior Manager to lead Planning transformation within our Supply Chain & Engineering practice for Life Sciences. This role requires guiding AI-driven transformation at the executive level, translating complex client needs into strategic plans and measurable outcomes.

Travel up to 75% and extensive collaboration across engineering, manufacturing, and sustainability domains are expected to deliver data-driven value for Life Sciences clients.

Qualifications

• Minimum 8 years of AI & Data experience, including solutioning, designing, or delivering AI & Data projects.
• Minimum 8 years of high-value consulting experience, including large-scale delivery with minimal oversight and proven ability to lead workstreams and meet deadlines.
• Experience leading senior-level (C-suite) conversations or managing senior-level stakeholders.
• Experience working within the Life Sciences Industry.

Responsibilities

• Shape vision and create opportunities for data & AI led business reinvention.
• Define and structure an organization's data and AI strategy to build and optimize data assets and AI technologies for growth and competitive advantages.
• Assess maturity of an organization's AI and data foundation and define building blocks for AI-first operating model.
• Create the business case, investment profile and roadmap to deliver on the strategy.
• Infuse Responsible AI and plan for ecosystem partnerships and operating model.

Skills

AI & Data

Executive leadership

Consulting experience

Life Sciences

Tools

AWS

Azure

Google Cloud

NVIDIA

Job description

Accenture is seeking a Senior Manager to lead Planning transformation within our Supply Chain & Engineering practice for Life Sciences. This role requires guiding AI-driven transformation at the executive level, translating complex client needs into strategic plans and measurable outcomes.

Travel up to 75% and extensive collaboration across engineering, manufacturing, and sustainability domains are expected to deliver data-driven value for Life Sciences clients.