2026 Co-Op, Drug Product Automation & Manufacturing Data

Moderna • Norwood, MA

3d • $20 - $60 • Onsite

About The Position

The Role: We are seeking a highly motivated Co-Op / Intern to support Global Drug Product Automation initiatives focused on manufacturing data standardization, PackML data modeling, and OEE (Overall Equipment Effectiveness) analytics. This role combines aspects from automation/controls engineering, manufacturing operations, and software/data engineering. The co-op will work on the integration of multiple, complex control systems, including Moderna’s existing Wonderware Drug Product SCADA system and various vendor-supplied production manufacturing fill-finish equipment (e.g., Syringe/Vial Fillers, Automatic Visual Inspection, Packaging, Room Monitoring and Warehouse) to contextualize industry-standard Organization for Machine Automation and Control (OMAC) PackML data structure and prototype reusable Overall Equipment Effectiveness (OEE) templates for manufacturing teams. This is a hands-on learning opportunity to understand Industry 4.0 concepts and how industrial automation data is transformed into meaningful manufacturing insights used by high-level systems such as SIMCA and a Unified Namespace (UNS). Why This Role Matters: This co-op will directly contribute to standardizing how manufacturing data is structured and consumed, enabling more consistent OEE reporting and better decision-making across drug product operations. The work will influence how automation data is shared with manufacturing teams and higher-level digital platforms. What Success Looks Like: By the end of the co-op, you will have: - A clear understanding of PackML implementation across multiple vendor skids - Documented findings on data consistency and gaps - One or more prototype OEE dashboards/templates - Recommendations on improving PackML data usability for manufacturing

Requirements

• Currently pursuing a Bachelor’s or Master’s degree in: Engineering (Chemical, Mechanical, Electrical, Automation, Industrial, or similar) preferred Computer Science, Software Engineering, or Data Engineering
• Comfortable working with structured data and learning industrial systems
• Strong analytical mindset with attention to detail
• Able to communicate technical concepts clearly to both engineers and non-engineers
• Curious, self-driven, and willing to ask questions
• This position is site-based, requiring you to be at Moderna’s site full-time.
• This position is not eligible for remote work.
• Candidates must already hold work authorization in US and be able to maintain that status without the need for future sponsorship.

Nice To Haves

• Coursework or experience related to: Manufacturing systems, automation, or industrial controls
• Data analytics or systems integration
• Interest in understanding manufacturing processes, not just software
• Familiarity with industrial or time-series data concepts
• Data & Integration PackML concepts and state models
• MQTT or event-driven data architectures
• Unified Namespace (UNS) concepts
• Time-series data structures
• Languages & Formats Python (data analysis, scripting)
• SQL (basic querying)
• YAML / JSON (configuration and data modeling)
• Basic understanding of REST APIs
• Visualization & Prototyping Power BI, Tableau, or similar dashboarding tools
• Jupyter notebooks or equivalent analysis tools
• Industrial Context PLC concepts (Rockwell, Siemens, B&R exposure is a plus)
• SCADA or HMI systems (Wonderware, Ignition, etc.)

Responsibilities

• Manufacturing Data & PackML Review and understand control system architecture of vendor manufacturing equipment
• Review and understand PackML data models to be implemented across multiple vendor manufacturing equipment
• Analyze PackML tag structures, state models, and data quality across platforms
• Learn and evaluate the purpose and value of Rockwell PackML library objects and their role in standardized data exchange
• Support understanding of a dedicated PLC used for vendor and drug product automation contextual data
• Gather and normalize PackML-based production data from SCADA systems
• Assist in defining OEE metrics (Availability, Performance, Quality) based on standardized data
• Prototype OEE dashboards or templates that can be reused across manufacturing lines
• Collaborate with manufacturing and automation engineers to validate assumptions and interpretations of data
• Gain exposure to AVEVA Wonderware SCADA and how it interfaces with vendor equipment
• Support data exchange to higher-level systems such as SIMCA and Unified Namespace (UNS) architectures
• Document findings, assumptions, and data models in a way that manufacturing teams can consume

Benefits

• Free premium access to meditation and mindfulness classes
• Subsidized commuter benefits
• Generous paid time off, including vacation, sick time, holidays, volunteer days, and a discretionary year-end shutdown
• Location-specific perks and extras

What This Job Offers

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