Job Description
We are a global biopharmaceutical leader with a portfolio of prescription medicines, oncology, vaccines and animal health products. We are driven by our purpose to develop and deliver innovative products that save and improve lives. With 69,000 employees operating in more than 140 countries, we offer state of the art laboratories, plants and offices that are designed to inspire our employees as we learn, develop and grow in our careers. We are proud of our over 125 years of service to humanity and continue to be one of the world’s biggest investors in Research & Development.
We are seeking a Senior Scientist to join our Digital Insights team within the Development Sciences and Clinical Supply (DSCS) Digital Technologies organization.Digital is the multiplier that will allow DSCS to deliver better experiments faster, efficient filing and launch, more robust supply chains and higher-confidence decisions across the portfolio.
The DSCS Digital Technologies organization is responsible for the invention and application of new digital tools/workflows to support scientists across drug substance development, drug product development and analytical development. We aspire to embed digital technologies into the fabric of DSCS culture to drive transformational impact. The tools that we develop are as the teams developing them, and in this Senior Configuration Engineer role, the successful candidate will leverage their expertise in working with ELN configuration and structured data design to enable standardized, high-quality data capture across CMC workflows. The person in this role will work across our company small molecule, biologics, and vaccines portfolio with an initial focus on helping deliver the staged implementation of a unified CMC data model through scalable ELN configuration.
The candidate will be tasked with leading the design, configuration, and governance of Admin Defined Templates (ADTs), Worksheets, and experiment templates within the Signals platform to ensure consistent, structured capture of experimental data at the source. This includes, but is not limited to, translating complex scientific workflows into reusable templates with embedded logic, aligning Signals configurations to enterprise data models, and enabling seamless integration with downstream analytics, machine learning, and regulatory systems. This role sits within the Digital Insights team which is working to digitally enable a decision engine for DSCS, by innovating solutions through strong partnership in the domains of Data Science, Data Analysis, Informatics, Multi-Omics, Predictive Science, and Data Engineering.
Responsibilities:
- Lead the design, configuration, and lifecycle governance of Signals configurational elements to standardize data capture across CMC workflows
- Align configuration development to the unified CMC data model and phased implementation roadmap
- Translate scientific workflows into scalable templates with embedded logic, validation rules, and ontologies
- Partner with scientists, SMEs, and digital product teams to drive adoption and ensure templates meet scientific and operational needs
- Ensure data quality, harmonization, and reusability, enabling integration with analytics, ML, and regulatory systems
- Establish and enforce standards for template design
- Contribute to continuous improvement of ELN configuration practices and broader DSCS digital transformation initiatives
Education Minimum Requirement:
- Ph.D. in Computer Science, Data Science, Molecular Modeling, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely-related field
- M.S. in Computer Science, Data Science, Molecular Modeling, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely-related field with at least 2 years of industrial/pharmaceutical or relevant experience
- B.S. in in Computer Science, Data Science, Molecular Modeling, Engineering, Chemistry, Physics, Biology, Pharmaceutical Sciences, or a closely-related field with at least 4 years of industrial/pharmaceutical or relevant experience
Required Experience and Skills:
- Experience configuring ELN platforms, with strong expertise in structured templates
- Demonstrated ability to translate scientific workflows into structured data designs, including controlled vocabularies, formulas, and validation rules
- Strong CMC domain knowledge across analytical, process, formulation, and drug substance/product development
- Experience supporting enterprise data model or platform implementations, including source-to-canonical data mapping
- Working knowledge of GxP requirements, data integrity principles (ALCOA+), and validated SDLC practices
- Excellent communication skills, demonstrated creativity, and effective 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
- Motivated to learn new skills, willingness to take on new challenges, and scientific curiosity
Preferred Experience and Skills:
- Hands-on experience configuring Revvity Signals ADTs at scale within an enterprise environment
- Experience leading or contributing to enterprise data model or data harmonization initiatives in pharma R&D/CMC
- Proficiency with Databricks, SQL, Python, or Spotfire for downstream data enablement
- Familiarity with ontologies and data standards (e.g., Allotrope, internal CMC vocabularies)
- Demonstrated leadership in driving standards adoption and establishing communities of practice
- Experience with data pipeline tools such as Databricks
- Experience with relational databases and SQL
- Experience with common process and analytical capabilities commonly utilized in pharmaceutical development
- Evidence of cross-functional collaborations
