Senior Manager – AI, Data, and Analytics

Abbott

Senior Manager leading AI, data, and analytics initiatives for corporate functions at Abbott. Shaping data strategies and ensuring data integrity for decision-making.

Posted 7/24/2026full-timeAbbott Park • Illinois • 🇺🇸 United StatesSenior💰 $129,300 - $258,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data architecture, analytics, and AI applications, with a strong focus on operationalizing data initiatives and delivering measurable business outcomes. Proven ability to communicate complex concepts to diverse stakeholders and lead cross-functional teams in a data-driven environment.

Highest-signal resume keywords

Data ArchitectureData Visualization ToolsDataOps PracticesAI Applications in BusinessLeadership and Stakeholder Influence

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsSQLPythonRData IntegrationData QualityMetadata ManagementData GovernanceAdvanced AnalyticsData Delivery Practices

Soft Skills

Business AcumenCommunication SkillsCross-Functional Team Leadership

Tools & Technologies

Power BITableauCloud Data PlatformsVector DatabasesRetrieval-Augmented Generation

Industry Keywords

Data Governance FrameworksData ObservabilityOperational ControlsEnterprise Reporting StandardsRisk Mitigation Strategies

Tech Stack

Tools & technologies

CloudPythonSQLTableau

About the role

Key responsibilities & impact

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, and time-to-insight.
Allocate resources effectively to ensure successful execution of data and analytics initiatives.
Track and report on the performance, adoption, and realized value of data and analytics products and initiatives (e.g., dashboards, regular stakeholder reviews, and post-implementation lessons learned.)

Requirements

What you’ll need

Minimum of 7–10 years of experience in data analytics.
Strong technical foundation in data architecture and analytics, including experience with data visualization tools (e.g., Power BI, Tableau) and advanced analytics tooling (e.g., SQL, Python, R).
Demonstrated experience defining and governing enterprise data architecture, including data integration, data quality, metadata, lineage, and data governance frameworks.
Strong experience with modern data delivery practices such as DataOps (CI/CD, automated testing, monitoring/observability, and documentation) in support of regulated, auditable environments.
Knowledge of AI, machine learning, and GenAI applications in business and financial analytics.
Strong business acumen with the ability to translate complex analyses into actionable recommendations.
Proven leadership skills, including experience influencing senior stakeholders and leading cross-functional teams.
Bachelor’s degree in data science, Statistics, Computer Science, Business Administration, or a related field.

Benefits

Comp & perks

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.