Principal Scientist in particulate materials characterization & digital sciences
AI in this role
Lead development of particulate characterization methods and AI-driven predictive tools for drug product manufacturing.
Use Your Power for Purpose
At Pfizer, our purpose is to deliver breakthroughs that change patients' lives. Central to this mission is our Research and Development team, which is dedicated to translating advanced science and innovative technologies into the therapies and vaccines that matter most. Whether you are involved in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, you will leverage cutting-edge design and process development capabilities to accelerate the delivery of best-in-class medicines to patients worldwide.
ROLE SUMMARY
The Drug Product Design & Supply (DPDS) organization is seeking a Principal Scientist in particulate materials characterization & digital sciences to advance the manufacturing science of solid oral dosage forms, including tablets, capsules, and multiparticulate systems. This role will focus on developing innovative experimental and digital approaches to characterize drug substances, excipients, drug-product intermediates, and drug product, generating the mechanistic understanding needed to accelerate pharmaceutical development and manufacturing.
Our goal is to enhance our material-sparing, predictive-science-based drug product development approaches to further enable robust formulation risk assessment and decision making. By combining advanced particulate-material characterization, laboratory automation, artificial intelligence (AI), and digital technologies, we generate key experimental data of high quality and scientific insights needed to support formulation development, process understanding and advancement of next generation predictive tools.
The successful candidate will lead the development of novel characterization methodologies and laboratory workflows, leveraging modern data science and AI tools to improve the understanding and prediction of particulate-material behavior. Close collaboration with formulation scientists, process modelers, process engineers, and data scientists will be essential to translate material understanding into improved product quality, manufacturing robustness, and development efficiency.
ROLE RESPONSIBILITIES
- Lead the development of innovative characterization methods for drug substances, excipients, drug-product intermediates and drug product from particulate to bulk scales to improve understanding of critical material attributes and process-relevant behavior.
- Apply artificial intelligence (AI), machine learning (ML), and advanced analytics to characterize particulate materials, extract insights from complex datasets, and enable predictive understanding of material behavior.
- Develop and implement automated and high-throughput characterization workflows, including integration of instrumentation into digital laboratory environments and robotic platforms
- Partner with process modelers and digital scientists to establish experimental data pipelines that support model-informed drug product development and manufacturing.
- Develop data analysis, visualization, and reporting workflows that facilitate rapid decision making and knowledge generation.
- Support Pfizer's strategic initiatives in digital development, advanced manufacturing, and laboratory automation.
- Collaborate closely with formulation scientists, process engineers, and modelers to connect material properties with process performance and product quality.
- Communicate scientific findings through technical reports, presentations, publications, patents, and external scientific forums.
- Collaborate with academic institutions, research organizations, technology providers, and equipment vendors to evaluate and implement emerging characterization technologies.
QUALIFICATIONS
Must Have
- PhD with at least 3 years of relevant experience, or MS with at least 9 years of relevant experience in Pharmaceutical Sciences, Chemical Engineering, Materials Science, Mechanical Engineering, or a related discipline. (Academic or industry)
- Demonstrated expertise in characterization of powders, particulate materials, granular systems, or related complex materials.
- Strong quantitative, analytical, and problem-solving skills with experience handling complex experimental datasets.
- Excellent organizational, interpersonal, written, and verbal communication skills.
- Demonstrated record of scientific publications, presentations, patents, or technology development.
Nice to Have
- Demonstrated experience in developing novel characterization methods, instrumentation, or measurement workflows.
- Familiarity with leveraging AI, machine learning, or other advanced data-science tools to characterize particulate materials and accelerate scientific decision making.
- Familiarity with laboratory automation, robotics, high-throughput experimentation, or digital laboratory solutions.
- Experience with programming and data analysis skills using Python, R, MATLAB, or similar tools.
- Knowledge of statistical methods, Design of Experiments (DoE), multivariate data analysis, and predictive modeling approaches.
- Familiarity with pharmaceutical manufacturing processes and the relationships between material attributes, process performance, and final product quality.
- Demonstrated ability to work effectively with multidisciplinary teams.
- Industry experience is preferred
PHYSICAL/MENTAL REQUIREMENTS
- Requires the ability to safely conduct laboratory work, including standing, walking, and handling laboratory materials and equipment.
- Requires analytical skills to perform complex data interpretation, mathematical analysis, scientific problem-solving, and computer-based data processing.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
- No non-standard work schedule, travel, or environmental requirements.
Relocation support available
Work Location Assignment: Hybrid-
The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.
Relocation assistance may be available based on business needs and/or eligibility.
Candidates must be authorized to be employed in the U.S. by any employer.
U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.
Research and Development
How we rate this
Principal Scientist in particulate materials characterization & digital sciences at Pfizer rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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- What's a project where you used Artificial Intelligence hands-on?
- Walk me through how you've used Machine Learning in your day-to-day work.
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- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
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