Data & AI Acceleration Manager (Raleigh, NC)

JT International S.A.

20h

About The Position

The Data & AI Acceleration Manager connects business priorities in an assigned function or market with the organization’s enterprise Data & AI strategy, governance, platforms and delivery model. Positioned within Digital & IT and aligned with the global Data, Analytics & Innovation team, this role serves as the entry point for Data & AI demand and ensures requests are qualified before delivery. The manager shapes business needs and owns initiatives from initial request through development, deployment, operational transition and adoption, helping teams use enterprise capabilities such as conversational AI, Microsoft 365 Copilot, Copilot Studio, the Central Data Lake Platform, and reporting and analytics solutions. The role owns the function or market Data & AI portfolio and backlog, guides initiatives through enterprise architecture and governance requirements, and drives adoption, literacy and responsible AI use. The manager coordinates business, IT, Data & AI teams and external partners, tracks usage and business value, and supports reusable solutions and shared learning across the organization. Within the first six months, the manager is expected to build trusted relationships with leadership and delivery partners, establish a clear view of demand, initiatives, priorities, governance and adoption opportunities, and take ownership of priority initiatives while establishing effective delivery, governance, reporting and adoption routines.

Requirements

At least 5 years of professional experience in Data & Analytics, business technology or solution delivery within a large multinational, ideally FMCG.
Proven accountability from demand intake and solution shaping through build, deployment and operational transition, working with internal teams and external partners.
Experience partnering with senior stakeholders to shape requests, challenge scope, develop business cases and prioritize portfolios.
Strong communication and influencing skills.
Practical understanding of enterprise data platforms, data models, analytics and reporting solutions, Generative AI, Microsoft 365 Copilot and Copilot Studio, sufficient to shape solutions, challenge designs and guide citizen development.
Strong project and delivery-management skills across the solution lifecycle, including planning, estimation, risks, dependencies, testing, deployment and reporting.
Proven experience delivering Machine Learning solutions, with practical understanding of data preparation, model development, evaluation, deployment and monitoring.
Understanding of data governance, data quality, privacy, information security and responsible-AI practices, including exposure to Legal, Data Protection and compliance reviews.
A college or university degree; a related field is preferred, such as Information Systems, Computer Science, Data Science, Engineering or Business Administration.
Fluent written and spoken English.
Ability to manage competing priorities and drive outcomes without direct authority in a matrixed, remote organization with dual reporting lines.

Nice To Haves

Experience in FMCG.
Postgraduate qualifications.
Project or programme management certifications.
Data & Analytics or AI certifications.
Fluency in a relevant local language.

Responsibilities

Own the function or market Data & AI backlog and its contribution to the three-year technology roadmap and annual strategic planning cycle.
Partner with stakeholders to define business problems, value, data needs and feasibility; classify requests into appropriate delivery routes; and jointly prioritize demand with DA&I.
Own end-to-end delivery of the Data & AI portfolio on time, within budget and to agreed scope, quality and business outcomes, coordinating business, IT, DA&I and external partners.
Ensure testing, release readiness, documentation and support models are in place.
Ensure solutions follow enterprise architecture, data management, security, integration and technology standards, and secure required approvals before build starts.
Promote the Central Data Lake Platform, Global Data Model and reusable components; reduce duplication; contribute reusable assets to the enterprise; and resolve deviations through governance channels.
Govern AI use cases from idea through production using the agreed AI scaling process, stage gates and AI Governance Guidelines.
Coordinate Legal, Data Protection, compliance, security and risk reviews; document approvals before deployment; and monitor transparency, human oversight, bias and quality controls and records of use after go-live.
Maintain an inventory of solutions and agents, including ownership, purpose and approval status.
Drive adoption of enterprise conversational AI and business agents, Microsoft 365 Copilot, Copilot Studio, self-service analytics and approved data platforms, tracking active usage and realized value.
Guide and govern citizen development so that business-built agents and solutions remain within approved guardrails.
Own Data & AI literacy building across the IT team and business population, including AI Academy completion, playbook-based guidance, training and community engagement.
Identify hackathon and AI Factory candidates, prepare business cases and supporting data, mobilize business participants, and share successful use cases and lessons across functions and the DA&I community.
Within the first six months, build relationships with functional or market leadership, business stakeholders, Data & AI teams, platform owners and delivery partners.
Within the first six months, establish a clear view of Data & AI demand, active initiatives, priorities, governance status and adoption opportunities.
Within the first six months, take ownership of priority initiatives and establish effective delivery, governance, reporting and adoption routines.