Senior Manager - AI, Data, and Analytics

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:

• Career development with an international company where you can grow the career you dream of.
• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

As the Senior Manager, AI, Data, and Analytics, you’ll lead enterprise data, analytics, and AI enablement initiatives supporting Corporate Functions (Finance, Procurement, Legal, Compliance, and M&A), enabling strategic decision-making and measurable business outcomes. You’ll shape a comprehensive data and analytics strategy, including governance models that ensure scalable, AI-ready solutions. In partnership with platform, integration, governance, and AI engineering teams, you’ll translate business demand into prioritized delivery, adoption, and value realization. The successful candidate will ensure data integrity, security, and privacy—combining technical expertise, business acumen, and leadership to deliver meaningful value.

What You’ll Work On

• Serve as a first point of contact for Corporate Functions on AI, Data, and Analytics tooling and capabilities, advising on best-fit solutions (enterprise platforms vs. productivity-embedded solutions) based on business use cases and risk considerations.
• Help operationalize intake-to-value delivery for AI/GenAI use cases (intake → assess data readiness → pilot → scale), including clear stage gates, ownership, and benefits tracking in partnership with business, risk, and engineering stakeholders.
• Partner with business leaders and BRMs to shape demand and translate priorities into data domains, analytics use cases, and measurable business outcomes.
• Incorporate data and GenAI initiatives into prioritized roadmaps with clear outcomes, dependencies, and data readiness, ensuring alignment with organizational strategic priorities.
• Define and enable agentic AI (e.g., copilots, task-oriented agents, and workflow-embedded AI) by establishing the data, architecture, and governance foundations that allow AI agents to safely reason, act, and integrate with enterprise systems.
• Partner with business leaders and external vendors establishing a data and analytics strategy and operating model (intake, prioritization, delivery, adoption, and value realization) for each function, including governance models that ensure scalable, AI-ready solutions.
• Evaluate and guide adoption of established and emerging technologies (e.g., cloud data platforms, vector databases, retrieval-augmented generation (RAG), advanced analytics, and real-time inference architectures) to enhance corporate capabilities.
• Promote enterprise reporting standards and governed semantic layers to ensure consistent definitions of key metrics across Corporate Functions.
• Improve reliability and trust through data observability and operational controls (monitoring, alerting, SLAs, and automated checks) in collaboration with platform and integration teams.
• Identify risks and support mitigation strategies impacting financial and operational performance.
• Communicate complex data, architecture, and analytics concepts to non-technical stakeholders in a clear, actionable manner.
• Continuously evaluate and improve data and analytics processes and methodologies to increase reliability, usability, an