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Principal Scientist, Innovation Management, Fremont CA

Job in Fremont, Alameda County, California, 94537, USA
Listing for: Boehringer Ingelheim GmbH
Full Time position
Listed on 2026-01-23
Job specializations:
  • Engineering
    Data Science Manager, Biotechnology
Job Description & How to Apply Below

Principal Scientist, Innovation Management, Fremont CA Description

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development, and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in several ways to foster a healthy working environment, meaningful work, mobility, networking, and work-life balance.

Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

The Principal Scientist, Innovation Management will act as a primary expert for upstream/drug substance development and manufacturing with a unique blend of expertise in biopharmaceutical upstream processes, digitalization, and data science. This role will identify and evaluate emerging technologies and companies that can enhance biopharmaceutical manufacturing. The incumbent will provide scientific and technical leadership to the team on both internal and external projects.

Duties & Responsibilities
  • Ensures direct report (intern & co-ops) safety, training, and supervision.
  • Responsible for effective management of a team of technical experts. This is an individual contributor Role.

Upstream/Drug Substance Development and Manufacturing:

  • Leads the development and optimization of upstream processes for biopharmaceutical production.
  • Oversees cell culture operations, including media development, bioreactor design, and scale-up processes.
  • Ensures compliance with regulatory standards and quality control measures.
  • Collaborates with cross-functional teams to integrate upstream processes with downstream and analytical development.

Digitalization and Data Science:

  • Implements digital tools and data analytics to enhance process understanding and control.
  • Develops and applies predictive models for process optimization and troubleshooting.
  • Utilizes machine learning and AI to drive continuous improvement in manufacturing processes.
  • Manages data integrity and ensures robust data management practices.

Scouting Technologies and Companies:

  • Identifies and evaluates emerging technologies and companies that can enhance biopharmaceutical manufacturing.
  • Conducts due diligence and feasibility assessments for potential technology acquisitions or partnerships.
  • Collaborates with global teams to integrate new technologies into existing processes.
  • Stays abreast of industry trends and advancements to maintain a competitive edge.

Leadership and Team

Collaboration:

  • Provides scientific and technical leadership to the upstream development team.
  • Mentors and develops team members, fostering a collaborative and high-performance culture.
  • Manages project timelines, budgets, and resources effectively.
  • Represents the company at industry conferences and scientific meetings.
Requirements
  • BS with ten-plus (10+) years’ experience in Chemical/Biochemical Engineering, Bioengineering, Biochemistry, Biology, or related scientific field.

OR

  • MS with six-plus (6+) years’ experience in Chemical/Biochemical Engineering, Bioengineering, Biochemistry, Biology, or related scientific field.

OR

  • PhD with three-plus (3+) years’ experience in Chemical/Biochemical Engineering, Bioengineering, Biochemistry, Biology, or related scientific field.
  • Thorough knowledge of biotechnology process development methodologies such as cell culture, aseptic techniques, bioreactor operation and development, column chromatography, filtration, and UFDF.
  • Knowledge of GMP biopharmaceutical manufacturing, including process validation and commercial manufacturing support.
  • Four-plus (4+) years’ experience in late-stage process development preferred.
  • Two-plus (2+) years’ experience leading in a matrixed environment preferred.
  • Two-plus (2+) years’ experience in data science, Machine learning, and statistical analysis skills
  • Excellent verbal and written communication skills.
  • Good documentation and presentation skills.
  • Proven skills building and maintaining productive relationships with…
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