Data & AI Strategy Manager/Senior Manager - Supply Chain & Engineering

Accenture•Chicago, NY

7d•Hybrid

About The Position

Accenture is seeking a Data & AI Strategy Manager/Senior Manager for its global Data & AI practice, focused on Supply Chain & Engineering (SC&E). The role serves as a strategic link between business leaders and technical teams, helping clients turn Data & AI solutions into measurable business outcomes and organizational transformation. The successful candidate will guide clients through the AI journey, from identifying opportunities and developing strategies to enabling execution and measuring impact. The position also supports practice growth through offering development, business development, and development of team skills and capabilities. The role is based in New York or Chicago and follows a hybrid work model, combining work from home with time in the office. Travel may be required and can range from 0% to 100%, depending on business needs and client requirements. The position requires a bachelor's degree or equivalent work experience, with the stated experience alternatives for associate’s degree holders. Accenture lists annual salary ranges by location, from $80,400 to $293,800, depending on the location and other factors. The posting is anticipated to remain open until 11/30/2026.

Requirements

At least 6 years of experience in Supply Chain, Engineering, Manufacturing, operations, or Digital Transformation, with a significant portion in Life Sciences, Pharmaceutical, Biotech, MedTech, or Healthcare industries.
At least 5 years of consulting experience in strategy, management consulting, technology consulting, or equivalent internal consulting, leading business transformation initiatives for Life Sciences clients.
At least 6 years of experience translating business challenges into technology-enabled solutions, including Data, Analytics, AI, Automation, or Digital platforms.
At least 5 years of experience leading workstreams or projects involving cross-functional business and technology stakeholders.
Bachelor's degree or equivalent (minimum 12 years of work experience). Candidates with an associate’s degree must have at least 6 years of work experience.
Applicants for US employment must have work authorization that does not now or in the future require visa sponsorship.

Nice To Haves

Experience with Life Sciences business processes, including GMP environments, regulatory compliance, Quality management, product development, manufacturing, or clinical supply chain.
Knowledge of industry platforms such as SAP, Kinaxis, o9, Blue Yonder, Siemens, PTC, Dassault, AVEVA, AspenTech, or similar Supply Chain and Engineering solutions.
Solid understanding of data governance, data management, and the AI solution lifecycle from strategy through implementation.
Ability to engage senior stakeholders, influence decision-making, and build trusted relationships across business and technical teams.
Experience developing business cases, defining KPIs, and measuring the impact of Data & AI initiatives.
Analytical mindset, structured problem-solving skills, and focus on delivering measurable value.
Excellent communication and presentation skills, including the ability to simplify complexity and engage diverse audiences.
Team-oriented leadership style and experience mentoring or coaching junior colleagues.
Flexibility and adaptability across multidisciplinary, global, and fast-paced environments.
Advanced degree in a relevant field.

Responsibilities

Lead Data & AI transformation initiatives, identify opportunities, shape strategies, and guide development and deployment of AI-powered solutions with technical teams.
Define and implement Data & AI strategies that enable Supply Chain & Engineering transformation and drive efficiency, resilience, and innovation.
Bridge business and technical stakeholders, align them, manage expectations, and enable successful solution delivery.
Design and support data governance models that establish data quality, availability, and compliance for scalable AI solutions.
Develop business cases and value frameworks, quantify impact, define KPIs, and support executive alignment and adoption.
Contribute to business development, including identifying opportunities, engaging clients, and creating tailored proposals and go-to-market strategies.
Mentor junior team members and promote knowledge sharing, skill development, and a high-performance consulting culture.
Contribute to practice growth by developing offerings and strengthening the team’s skills and capabilities.