Principal Scientist, DSCS Digital Technologies-Laboratory Automation, Time Series Data Strategy (Hybrid)
Role details
Job location
Tech stack
Job description
- Work at the intersection of multiple disciplines, collaborating with experts in automation, data science, modeling, IT, and the CMC community at large
- Lead high-impact projects from concept through deployment, working across teams and stakeholders to deliver meaningful outcomes
- Continuously improve existing digital technologies and automation platforms to enhance performance, usability, and reliability
- Empower others by providing hands-on partnership, support, troubleshooting, and training to scientists using these technologies
Requirements
- A Ph.D. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Material Science or a closely-related field with at least 6 years of relevant experience
- A M.S. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Material Science or a closely-related field with at least 8 years of relevant experience
- A B.S. in Chemistry, Biochemistry, Engineering (i.e., Mechanical, Electrical, Chemical), Physics, Biology, Pharmaceutical Sciences, Material Science or a closely-related field with at least 10 years of relevant experience
Required Experience and Skills
- Highly motivated, technology-centric scientist or engineer with a demonstrated track record of modernizing pharmaceutical development practices that include biologics, vaccines, and small molecule modalities.
- Demonstrated experience with time series data, continuous data streams, scientific data engineering, laboratory or pilot plant automation, process informatics, PAT, or related data-rich technology 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 multiple stakeholder groups.
- Strong understanding of how data classifications, data dimensions, instrumentation, workflows, users, criticality, and lifecycle considerations influence solution design and prioritization.
- Ability to work across multiple IT product lines and enterprise capabilities while balancing near-term business needs with sustainable long-term support models.
- Excellent communication skills, demonstrated creativity, effective interpersonal skills, and ability to influence without direct authority in a matrixed environment.
- Ability to lead complex, cross-functional projects under compressed timelines in a dynamic environment.
Preferred Experience and Skills:
- Extensive experience with historians or time series platforms, including requirements definition, evaluation of alternatives, migration strategy, contextualization, or data access patterns.
- Familiarity with modern industrial and laboratory data communication standards and patterns, including OPC, unified namespace concepts, ontology structures, asset models, metadata models, and contextualized data products.
- Experience designing solutions for persistent time series data, GMP-aware systems where appropriate, and flexible access patterns for scientific, engineering, modeling, and operational consumers.
- Experience with laboratory and pilot plant data sources such as sensor data, reactor data, offline, on-line, and in-line analytical data, scalar/vector/array/cube data structures, and dimension-plus-time data representations.
- Background in data engineering, cloud or enterprise data platforms, data modeling, Python, R Studio, SQL, Databricks, visualization tools, API-based integration, or related technologies.
- Experience evaluating, developing, or deploying digital and data-rich methodologies that support process and product understanding, batch analysis and monitoring, and/or CMC decision-making.
- Demonstrated track record of leading teams in a cross-functional, collaborative manner that span automation, IT, data science, modeling, process, product, and analytical development, and manufacturing.
- Motivated to learn new skills, take on new challenges, and bring scientific curiosity to ambiguous, enterprise-scale data problems., Adaptability, Adaptability, Analytical Instrumentation, Automation, Biochemistry, Biopharmaceutical Industry, Business, Cross-Functional Teamwork, Data Access, Data Analysis, Data Engineering, Data Science, Digital Technology, Enterprise Data, Innovation, Innovative Thinking, Laboratory Automation, Leadership Mentoring, Pharmaceutical Development, Pharmaceutical Process Development, Pharmaceutical Sciences, Professional Collaboration, Project Prioritization, Quality by Design, Real Time Data {+ 2 more}
Benefits & conditions
Pulled from the full job description
- 401(k)
- Health insurance
- Vision insurance
- Dental insurance
- Paid holidays
- Visa sponsorship, We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.
Learn more about your rights, including under California, Colorado and other US State Acts
The salary range for this role is $173,200.00 - $272,600.00 This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.
The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.