Principal Scientist, DSCS Digital Technologies–Laboratory Automation, Time Series Data Strategy

Overview

Principal Scientist position within DSCS Digital Technologies (DDT) in Development Sciences and Clinical Supply (DSCS).

Location:

Rahway, NJ or West Point, PA. The role focuses on identifying, developing, and deploying digital and data-rich technologies to improve process, product, and analytical understanding across small molecule, biologics, and vaccine portfolios. The DSCS Digital Technologies team aims to embed advanced digital capabilities into the laboratory and data ecosystems to accelerate pharmaceutical development.

• Design and implement lab-of-the-future technologies that integrate robotics, analytical instrumentation, and software into cohesive, high-performing solutions.
• Partner with researchers to understand experimental needs and translate them into scalable digital workflows.
• Work at the intersection of automation, data science, modeling, IT, and CMC to deliver cross-disciplinary solutions.
• Lead high-impact projects from concept through deployment across multiple teams and stakeholders.
• Continuously improve digital technologies and automation platforms for performance, usability, and reliability.
• Provide hands-on partnership, support, troubleshooting, and training to scientists using these technologies.
• Define and implement strategy for time series data collection, processing, visualization, historization, contextualization, and consumption across real-time, near-time, and post-batch contexts.
• Establish scalable platforms and prioritization principles that align short-term business needs with long-term enterprise strategies, including historian requirements, persistent time series data, and modern data standards (e.g., OPC, MQTT).

• Ph.D. in Chemistry, Biochemistry, Engineering (Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Material Science or closely-related field with at least 6 years of relevant experience.
• M.S. in the same fields with at least 8 years of relevant experience.
• B.S. in the same fields with at least 10 years of relevant experience.

• Motivated, technology-centric scientist or engineer with a track record in modernizing pharmaceutical development practices across biologics, vaccines, and small molecules.
• Experience with time series data, continuous data streams, scientific data engineering, automation, process informatics, PAT, or related data-rich ecosystems.
• Ability to architect and communicate scalable approaches for real-time, near-time, and post-batch data collection, processing, visualization, historization, contextualization, and consumption.
• Experience translating scientific and operational needs into data requirements, technical requirements, user stories, or solution architectures across stakeholders.
• Strong understanding of data classifications, data dimensions, instrumentation, workflows, users, criticality, and lifecycle considerations in solution design.
• Ability to work across multiple IT product lines and enterprise capabilities while balancing near-term needs with sustainable long-term support.
• Excellent communication, creativity, interpersonal skills, and ability to influence in a matrixed environment.
• Ability to lead complex, cross-functional projects under compressed timelines in a dynamic environment.

• Extensive experience with historians or time series platforms, including requirements definition and migration strategies; contextualization and data access patterns.
• Familiarity with modern industrial and laboratory data standards and patterns (OPC, unified namespace, ontology structures, metadata models, contextualized data products).
• Experience designing solutions for persistent time series data, GMP-aware systems, and flexible data access for scientific, engineering, modeling, and operational users.
• Experience with laboratory and pilot plant data sources (sensor, reactor, offline/online/in-line analytics) and time-dimension data representations.
• Background in data engineering, cloud or enterprise data platforms, data modeling, Python, R, SQL, Databricks, visualization tools, and API integration.
• Track record of leading cross-functional teams across automation, IT, data science, modeling, process, product, and manufacturing.

• Travel: ~10%
• Relocation:
  Domestic/International;
  Visa sponsorship available
• Shift: Day