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Senior Scientist (Computational) Process Modeling and Engineering Technology

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**Senior Scientist (Computational) Process Modeling and Engineering Technology**

**Job Description Summary**

The Global Parenteral Product Development team in PCOE (Worldwide R&D), Pfizer seeks a Senior Scientist (PhD level) to develop new mathematical / computational tools to support the development of sterile drug-dosage forms. The successful candidate will be able to use a wide range of statistical, mathematical and computational techniques to solve industrial research problems related to pharmaceutical manufacturing and will be accountable for development and deployment of novel process-focused Artificial Intelligence capability and for delivery of high impact soft sensor and Advanced Process Control solutions. Experience with a variety of statistical, mathematical, and computational techniques is required, such as Multivariate Data Analysis, Design of Experiments / Response Surface Methodologies, Multivariate Image Analysis, Advanced process control tools, Soft sensors and Artificial Intelligence tools.

Applicants must have a doctoral (PhD / Ph.D.) degree in Chemical Engineering, Mechanical Engineering, Pharmaceutical Engineering, Physical Sciences, Mathematics, or related discipline with a focus on computational modeling, industrial data analytics and AI. Close collaboration with Pfizer project scientists is essential - candidates must have excellent communication skills and be able to identify opportunities to develop and implement Advanced Analytics, Soft Sensors, Artificial Intelligence and Advanced Process Control solutions/capabilities across PCoE to achieve actionable insights and enable continued improvement for pharmaceutical manufacturing and quality operations.

**Major duties and requirements**

+ Work with Pfizer project scientist to understand the challenges and needs when developing drug-dosage forms (sterile injectables, solutions, suspensions, multi-particulate systems, etc.).

+ Work with pharmaceutical product design and the device design scientists / engineers to understand the design specifications, end-use objectives and requisite characteristics, risk involved during use, etc.

+ Using a variety of advanced analytics and computational techniques to develop predictive tools and models to support drug development/manufacturing efforts for the Pfizer portfolio including, but not necessarily limited to Multivariate Data Analysis, Design of Experiments / Response Surface Methodologies, Multivariate Image Analysis, Advanced process control tools, Softy sensors and AI / Machine Learning tools and techniques.

+ Understand business opportunities and identify and prioritize highest impact advanced analytics and control, artificial intelligence, machine learning and Industrial Internet of Things solutions. Apply engineering and scientific theory, modeling tools, and experimental skills using data-rich lab/pilot/manufacturing instrumentation or process analyzers information to improve process understanding and facilitate real-time process monitoring and control. Drive development and support implementation of mathematical models and digital twins.

+ Identify opportunities to use engineering knowledge and computational tools to help solve projects challenges. Be able to work independently, with minimal supervision, to define the problem statement, then develop and execute a modeling work plan to solve the issue. Effectively manage complex projects and priorities.

+ Plan and execute experimental studies in collaboration with experimental experts to support/validate modeling efforts. Work with Pfizer scientists to apply and implement modeling tools into project workflows.

+ Communicate and present results internally at meetings and, on occasion, at external forums. Present scientific results to a diverse audience through data analysis and visualizations.

+ Support Pfizer's key technology platforms: sterile injectables, solutions, suspensions, multi-particulate systems, etc., via computational modeling.

+ Work with external partners (e.g., universities, research organizations) and vendors (e.g., software companies) to execute and deliver well-defined modeling projects.

**Main Responsibilities**

+ Under the guidance of external partners in process consulting and customizeddigital solutions, champion internally the definition and roll out of sound process engineering approaches in the product development and tech transfer within the organization.

+ As an internal champion in process engineering activities, work with formulation development, tech transfer teams, and device design teams, via hands-on involvement, to understand various internal protocols in product life cycle journey

+ Help define product wise, process engineering strategies and accordingly, the needs in process analytics and process modeling capabilities from ground level perspectives

+ Facilitate and aid in the development, knowledge transfer and rollout of relevant capabilities by the partner organizations, to meet internal needs

+ Guide teams as an individual contributor and as an expert in the adoption of such approaches across various product needs across the product life cycle

+ Lead efforts in helping develop appropriate internal mechanisms for adoption of process engineering capabilities and their incorporations into FDA submissions as a routine

+ Support routine engineering needs for product development

**Preferred skills and experience**

+ Doctoral degree Chemical Engineering, Mechanical Engineering, Pharmaceutical Engineering, Physical Sciences, Mathematics or related discipline.

+ Strong interest and Hands-on experience in key technical areas, including process analytics and control, data science, advanced multivariate data analysis, machine learning and artificial intelligence. Relevant hands-on industrial experience (3- 5 years, preferably pharma) in providing solutions to complex technical problems applying scientific approaches.

+ Familiarity with and understanding in leveraging modeling and simulations for process development and tech transfer needs. Demonstrated initiative in developing and implementing innovative solutions.

+ Be comfortable being hands-on and taking a deep dive into novel technical areas when required, to achieve broader objectives. His creative, innovative, and dynamic. Has an excellent synthetic and analytical mind and an aptitude for problem solving.

+ Be a good listener, understanding the needs of non-engineer internal customers. Excellent oral communication, technical writing, and interpersonal skills.

+ Good teaming skills and ability to work with wide range of technical teams and projects, internal and external partners.

+ Working knowledge of data analytical approaches. Familiarity with industrial process control, automation systems and advanced process control platforms (including DeltaV and ASPEN). Familiarity with data historian platforms (such as OSI PI), and real-time communication protocols (such as OPC, ODBS and MQTT)

+ Familiarity with Big Data analytics and control platforms (such as PharmaMV, SIMCA, Statistica, Minitab...)

+ Proficient in one or more of the following programming environments: Python, R, Matlab, JAVA, Spark. Familiarity with key Data Science software suites (like Tibco and Spotfire) and cloud based platforms

+ Expertise in Artificial Intelligence algorithms, such as Deep Learning, Neural Networks, and latent variable modelling for time series, root cause analysis and anomaly detection

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

Research and Development

Posted: 2021-06-11 Expires: 2021-07-12
Sponsored by:
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