About The Position
The Senior Scientist will join Development Sciences and Clinical Supply Digital Technologies to help build data-rich, connected laboratory environments. The team uses robotics, process analytical technology, high-throughput technologies, instrumentation, and integrated systems to connect physical laboratory work with digital data and workflows. The role supports chemistry, manufacturing, and controls activities across small molecule, biologics, and vaccine development, helping create FAIR, AI-ready scientific data ecosystems that accelerate research and improve scientific decision-making and reuse of knowledge. The position focuses on integrating, orchestrating, and visualizing laboratory systems and workflows using industry-standard and emerging technologies. The Senior Scientist will work across laboratory automation, digital engineering, IT, and scientific teams to deliver scalable solutions connecting laboratory equipment, automation systems, and data pipelines. The role involves independently owning technical solutions and advancing automated, connected laboratories.
Requirements
- Ph.D. in a listed or closely related field, with expected graduation no later than December 2026; or an M.S. in a listed or closely related field plus at least 2 years of relevant experience; or a B.S. in a listed or closely related field plus at least 4 years of relevant experience.
- Proficiency in Python and/or R programming.
- Comfort working in development environments such as Jupyter, Posit/RStudio, or VS Code.
- Experience with ETL/ELT processes and building data pipelines in a scientific or pharmaceutical context.
- Familiarity with version control systems such as Git/GitHub and collaborative software development practices.
- Understanding of (bio)pharmaceutical process research and development, drug product development, and/or analytical development.
- Excellent communication, creativity, and interpersonal skills.
- Ability to deliver complex solutions under compressed timelines in a dynamic environment.
- Ability to work in a team environment with cross-functional interactions.
- Demonstrated ability to work independently and entrepreneurially on cross-functional teams.
- Demonstrated scientific ability through publications and presentations at scientific conferences.
Nice To Haves
- Understanding of knowledge representation and reasoning techniques.
- Working knowledge of ontology design, FAIR principles, data and metadata standards, and scientific data management practices.
- Understanding of semantic modeling, knowledge representation, and scientific data contextualization approaches.
- Familiarity with life-science data standards, including Allotrope, CDISC, or comparable frameworks.
- Experience working with heterogeneous scientific data sources and integrating information across multiple systems or domains.
- Experience connecting heterogeneous data sources and resolving differences in terminology, structure, and quality.
- Ability to model concepts, entities, relationships, and rules in a machine-readable way.
- Familiarity with ontology frameworks or standardized data models such as Allotrope Simple Model, ISA-88, or OPC-UA, and experience mapping instrument data to structured schemas.
- Understanding of data science and AI/ML concepts and their application to data contextualization.
- Background leveraging data engineering and data science technologies, including digital integration of analytical instrumentation.
- Experience researching new technologies and identifying, developing, and deploying digital and data-rich methodologies.
- Wet-lab experience in (bio)pharmaceutical drug substance, drug product, and analytical research and development.
- Motivation to learn new skills, willingness to take on new challenges, and scientific curiosity.
Responsibilities
- Integrate instrument and equipment platforms with semantic context and data systems to enable end-to-end digital workflows.
- Collaborate with experts in automation, data science, modeling, IT, knowledge capture, and chemistry, manufacturing, and controls.
- Partner with researchers to understand experimental needs and translate them into scalable digital workflows.
- Lead high-impact projects from concept through deployment, coordinating across teams and stakeholders.
- Develop automation systems that integrate robotics, instrumentation, equipment, and software into cohesive solutions.
- Continuously improve automation platforms to enhance performance, usability, and reliability.
- Provide hands-on partnership, support, troubleshooting, and training to scientists using the technologies.
Benefits
- Medical, dental, and vision healthcare and other insurance benefits for employees and family.
- Retirement benefits, including 401(k).
- Paid holidays, vacation, and compassionate and sick days.
- Eligible for annual bonus and long-term incentive, if applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
