Data & Lab Automation Scientist – Drug Product Development

GSK•Upper Providence, PA

About The Position

This role is for someone who bridges the lab bench and digital systems, with a background in formulation and drug product development and hands-on lab experience. The ideal candidate is excited about optimizing experimental workflows through data and automation, can understand processes deeply, identify automation opportunities, and partner with vendors to bring complex custom solutions to life.

Requirements

3+ years of hands-on experience in lab and data automation
Lab automation proficiency: Experience with liquid handling platforms (Hamilton or Tecan) design, scope, and execute automated workflows
Vendor management experience: Track record of working with external vendors on complex custom automation projects, from requirements definition through execution and troubleshooting
Lab experience: Current or recent hands-on laboratory work in a pharmaceutical, biotech, or analytical chemistry environment
Data and lab automation mindset: Comfortable with concepts around data automation, data capture architecture, and dashboarding; understanding of how to translate experimental workflows into structured data systems

Nice To Haves

Hands-on experience with laboratory autonomous mobile robots, including integration, configuration, orchestration, and troubleshooting.
Experience with data management practices in pharmaceutical drug product development
Proficiency in SQL and one or more programming/analytics languages: Python, JavaScript, R
Experience designing or implementing data visualization dashboards to support decision-making: RShiny, Spotfire, Tableau
Familiarity with data extraction from laboratory instrumentation and integration into centralized data systems
Knowledge of digital lab solutions (ELN best practices, data standards, regulatory considerations in pharma data management)

Responsibilities

Drive lab automation strategy: Scope, design, and implement automated workflows to increase throughput and data quality in drug product studies
Enable vendor partnerships: Scope and manage complex custom automation projects with external vendors, translating scientific needs into technical specifications and ensuring successful implementation
Collaborate across teams: Work with drug development experts, analytics teams, and instrumentation specialists to define requirements for ELN templates, dashboards, and data capture systems that support automated workflows
Streamline data flows: Contribute to automating data and information flows during experimental studies—from instrument data extraction to system integration, storage and visualization—reducing manual entry and improving data integrity
Build organizational capability: Share expertise in lab and data automation best practices and help standardize approaches across groups