OpEx Data Analyst I

Abbott • Plymouth, MN

3d • $50,700 - $101,300 • Onsite

About The Position

This position works out of our Plymouth, MN location for our Electrophysiology medical device business. In Abbott’s Electrophysiology (EP) business, we’re advancing the treatment of heart disease through breakthrough medical technologies in atrial fibrillation, allowing people to restore their health and get on with their lives.

What You’ll Work On
Support the development of EP’s Industry 4.0/AI/Automation foundation by building reliable, standardized data structures and insights that improve visibility into manufacturing and business performance. The role focuses on enabling data-driven productivity across production lines and core processes by supporting data collection, cleaning, integration, and basic pipeline development—while contributing to consistent data definitions, governance, and repeatable analytical workflows.

Rather than leading large-scale system deployment, this role helps establish the data backbone and decision logic that determines where digital and AI solutions create measurable value (e.g., GMI improvement, COGS reduction, delivery performance, and NPI scalability). The analyst ensures operational data is accessible, accurate, and actionable, enabling teams to identify inefficiencies, standardize Management Operating System (MOS) execution, and scale best practices across sites and value streams.

Data Foundations for Industry 4.0 (Primary Focus)
Supports the collection, cleaning, and structuring of manufacturing and operational data (e.g., throughput, cycle time, downtime, yield).
Build simple, reliable datasets that enable consistent measurement of productivity across sites and value streams.
Assists in establishing standardized data definitions to reduce variation in how metrics (e.g., OEE, lead time, scrap) are calculated and interpreted.
Contributes to defining “how EP works with data” in a standardized way.

Data-Driven Productivity Insights
Develops basic reports, dashboards, and visualizations to highlight inefficiencies in production lines and business processes.
Identifies trends, patterns, and anomalies that impact margin (GMI), cost (COGS), delivery performance, and capacity.
Supports root cause analysis by preparing structured datasets for problem-solving teams (e.g., Lean / MOS routines).

Industry 4.0/AI/Automation Use Case Identification
Assist senior team members in evaluating where digital, data, or AI solutions could improve productivity.
Build and integrate AI powered solutions, including agentic workflows
Helps document early-stage use cases informing decision logic to deploy at scale.
Leverage AI-assisted development tools (Claude, Codex, Cursor, GitHub Copilot) to accelerate delivery of transformational productivity improvements

Pipeline & Data Process Support
Assists in maintaining simple data pipelines and workflows for recurring reporting and analysis.
Supports automation of manual data collection and reporting processes to increase efficiency and reduce errors.

Business Collaboration (Operations-Focused)
Works with operations, engineering, and continuous improvement teams to understand process challenges.
Supports MOS (Management Operating System) routines with accurate and timely data.

Governance, Security & Compliance
Assists in applying data governance standards, including basic access controls and documentation.
Supports compliance with relevant frameworks (ISO 27001, ISO 42001, ISO 8000, etc.) as defined by the organization.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Data Science, AI. Computer Science, AI, software engineering or disciplines including Databases, Mathematics, Statistics, Physics, Machine Learning, Robotics or Engineering.
• Minimum 1 year experience with degree; or sufficient transferable experience to demonstrate functional equivalence to a degree
• Training using statistical analysis
• Basic experience of database application
• Basic knowledge of several tools (such as M365 Suite, Copilot, Databricks, SAP, Azure ML, OpenAI, other Generative Pre-trained Transformers (GPT)

Nice To Haves

• Prior experience/education in life sciences or healthcare preferred
• Experience building and integrating AI-powered solutions into production applications (including LLM integrations, prompt engineering, stacks, and APIs)
• Exposure to agentic AI frameworks such as Databricks, AWS, CrewAI, Agno, or similar AI orchestration frameworks

Responsibilities

• Supports the collection, cleaning, and structuring of manufacturing and operational data (e.g., throughput, cycle time, downtime, yield).
• Build simple, reliable datasets that enable consistent measurement of productivity across sites and value streams.
• Assists in establishing standardized data definitions to reduce variation in how metrics (e.g., OEE, lead time, scrap) are calculated and interpreted.
• Contributes to defining “how EP works with data” in a standardized way.
• Develops basic reports, dashboards, and visualizations to highlight inefficiencies in production lines and business processes.
• Identifies trends, patterns, and anomalies that impact margin (GMI), cost (COGS), delivery performance, and capacity.
• Supports root cause analysis by preparing structured datasets for problem-solving teams (e.g., Lean / MOS routines).
• Assist senior team members in evaluating where digital, data, or AI solutions could improve productivity.
• Build and integrate AI powered solutions, including agentic workflows
• Helps document early-stage use cases informing decision logic to deploy at scale.
• Leverage AI-assisted development tools (Claude, Codex, Cursor, GitHub Copilot) to accelerate delivery of transformational productivity improvements
• Assists in maintaining simple data pipelines and workflows for recurring reporting and analysis.
• Supports automation of manual data collection and reporting processes to increase efficiency and reduce errors.
• Works with operations, engineering, and continuous improvement teams to understand process challenges.
• Supports MOS (Management Operating System) routines with accurate and timely data.
• Assists in applying data governance standards, including basic access controls and documentation.
• Supports compliance with relevant frameworks (ISO 27001, ISO 42001, ISO 8000, etc.) as defined by the organization.

Benefits

• 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
• Medical, dental, vision, wellness and occupational health programs
• Paid time off
• 401(k) retirement savings with a generous company match

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level