Job Description

The Senior Scientist, SID Predictive Sciences provides leadership, guidance, and alignment for the development and deployment of e nd-to-end Predictive Sciences and the adoption and implementation of these predictive tools within early and late-stage programs to effectively support the S ID / PSSM business strategy The incumbent is responsible for the following key activities: Supporting and coordinating activities for SID Predictive Sciences by orchestrating activities across four work streams that include Digital Design, Digital Lab, Digital Manufacturing and Data Core. Work with Pfizer scientists to develop understanding of material properties, dosage form identification, stability, and manufacturing processes used in SI dosage form design and manufacture (liquids, suspensions, emulsions, lyophilized products, combination products, etc.) and apply material characterization and computational tools in support of formulation and process design, optimization, and troubleshooting, and dosage form quality attributes. Coordinate activities to identify opportunities to use engineering knowledge and computational tools to help solve complex project challenges. Be able to work in matrix environment supporting a team of scientists with minimal supervision, to define the problem statement, then develop and execute a modeling work plan to solve the issue. Using a variety of computational techniques, develop predictive tools and models to support drug development/manufacturing efforts for the Pfizer portfolio. Modeling techniques include (but are not limited to): discrete element method (DEM), computational fluid dynamics (CFD), process models and flowsheets, statistical techniques, population-balance models (PBM), and first-principles engineering models. Partner and influence Sterile Injectable Design teams through late-stage project and co-development milestones to incorporate design thinking into program activities, including clinical (when appropriate) and commercial formulation identification and process selection, stability risk assessments, products manufacturing, technology transfer to commercial sites, and/or registration activities. Communicate and manage technical and business risks to senior management. Work with global colleagues / leaders to promote application of computational models and digital tools in SI products development workflows. Drive the development of state-of-the-art computational modeling and characterization tools. Summarize, communicate, and/or present results internally and externally at leading scientific conferences and scientific journal publications. Present scientific results to a diverse audience through engaging data analysis and visualizations. Work with external partners (e.g., universities, research organizations) and vendors (e.g., software companies) to execute and deliver well-defined modeling or characterization projects. Develop and deploy Predictive / Data Science workflows across SID in support of project objectives. Develop and maintain best practices for digital activities in SID through a network of key internal and external experts. Report regularly to SID Leaders / Digital Sponsors. Establish long-term and short-term objectives for the projects he/she leads. Establish an effective framework that will support and ensure the broader adoption of Predictive / Data Sciences and Solutions within SID workflows. Partner with SID leaders in securing the right resources to integrate Digital accelerators within the respective workflows. BASIC QUALIFICATIONS Doctorate degree (Ph.D.) in Chemical Engineering, Mechanical Engineering, Pharmaceutical Engineering, Physics or Physical Sciences, or related discipline, with relevant educational background in computational modeling (experience with CFD, FEA or other numerical analysis, with an ability to work with a mainstream CFD software). At least 5 years research experience in a related industrial/academic setting with a minimum of 2 years of relevant experience in pharmaceutical or related industry. Research must be focused on computational modeling applied to fluid flows and/or multiphase flows. Strong interest and a relevant hands-on industrial experience in providing solutions to complex technical problems applying scientific approaches. Strong understanding of engineering fundamentals, including but not limited to fluid mechanics and heat and mass transfer. Knowledge of advance process control concepts, including real-time monitoring of critical process attributes and implementing proactive measures. Familiarity with and understanding in leveraging modeling and simulations for process development and tech transfer needs. Demonstrated initiative in developing and implementing innovative solutions. Comfortable taking a deep dive into novel technical areas when required, to achieve broader objectives. Creative, innovative, and dynamic. Has an excellent synthetic and analytical mind and an aptitude for problem solving. Good listener, understanding the needs of non-engineer internal customers. Excellent oral communication, technical writing, and interpersonal skills. Good teamwork skills and ability to work with wide range of technical teams and projects, internal and external partners. Working knowledge of data analytical approaches. Demonstrated Programming experience (Python, MATLAB ). Fluent in English. PREFERRED QUALIFICATIONS Ability to influence and collaborate with peers. Demonstrated ability to coach / interact with others colleagues to achieve meaningful outcomes and create business impact. Ability to lead projects in strong collaboration with Digital and Business Partners across Pfizer. Excellent communication skills and the ability to indirectly influence key partners and stakeholders

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