Amgen
Process Development Senior Scientist - Pre-Pivotal Drug Product Technologies
US - California - Thousand Oaks · Senior
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About the role
- Join Amgen's Mission of Serving Patients
- At Amgen, if you feel like you're part of something bigger, it's because you are.
- Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases.
Responsibilities
- Develop and characterize liquid and lyophilized formulations for biologics, with particular emphasis on biologics drug product formulation, handling, and lab-scale sterile filling.
- Build process understanding across unit operations to support scalable drug product development.
- Investigate biologics-relevant CQAs (e.g., aggregation, fragmentation, charge/size variants, subvisible particles, surface interactions) to inform formulation and process design decisions.
- Author technical documents, control-strategy inputs, risk assessments, IND/CTA regulatory sections, and tech transfer packages.
- Support internal and external technology transfer activities, including collaboration with CMOs/CDMOs, batch record review, process fit assessments, person-in-plant support, and troubleshooting during manufacturing campaigns.
Requirements
- Doctorate degree PhD OR PharmD OR MD
- Master's degree and 3 years of Scientific experience
- Bachelor's degree and 5 years of Scientific experience
- What you can expect from us
Nice to have
- PhD in Pharmaceutics, Biotechnology, Biochemistry, or related field with 2-4 years of postdoc or industry experience.
- Proven experience in formulation development, stability testing, and fill/finish operations for biologics
- direct biologics drug product formulation experience is strongly preferred.
- Demonstrated understanding of biologics drug product development considerations, including protein degradation, quality attributes, and product/process comparability.
- Experience integrating formulation, stability, and analytical data to advance biologics candidates from discovery or preclinical development into clinical manufacturing is highly desirable.
- Experience implementing laboratory automation, workflow digitization, AI/ML (e.g., LLMs, in silico tools) or electronic data capture to improve R&D productivity.
- Strong foundation in analytical and biophysical techniques relevant to biologics and biologics (e.g., UPLC/HPLC, SEC, IEX, RP-HPLC, HIC, CE-SDS, subvisible particle analysis, etc.).
- Familiarity with clinical-stage development, manufacturability, and risk-based decision-making.
Compensation
- 126,066.05USD -170,559.95 USD
Benefits
- Apply machine learning, AI, laboratory automation, and advanced data science to predictive modeling, workflow acceleration, and decision-making.
Company info
- Career Category Operations Job Description Join Amgen's Mission of Serving Patients At Amgen, if you feel like you're part of something bigger, it's because you are.
- If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team.
- What we expect of you We are all different, yet we all use our unique contributions to serve patients.
Equal opportunity
- Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
- Please contact us to request accommodation.
- Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.
- We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
Visa & Work Authorization
- Sponsorship for this role is not guaranteed.
This listing is sourced directly from Amgen's careers page and normalized into a canonical job model.