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 Senior 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 03 years of relevant experience, or MS with relevant industrial experience, in Pharmaceutical Sciences, Chemical Engineering, Materials Science, Mechanical Engineering, or a related discipline with 7 to 9 years of experience

• 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.

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:On Premise

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.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available onPfizer Careers.