Data Scientist Hybrid Modeling & Process control

Job Description

Manufacturing Intelligence organization within Pfizers Global Technology & Engineering (GTE) drives Pfizer Global Supply toward Industry 4.0 capability through Big Data, Process Analytical Technology, Advanced Process Control, Process Modelling, Artificial Intelligence and Advanced Robotics.The Manufacturing Intelligence organization identify and deliver high-value transformational opportunities focused on process insight and control of manufacturing assets and processes with the potential for substantially reducing cost and cycle time and increasing robustness and productivity.Within the Manufacturing Intelligence organization one of the teams (MI Data Analytics) is responsible for providing expert advanced data analytics and modelling support. This team works in close partnership with all other Manufacturing Intelligence teams, providing supplementary advanced analytics expertise across a range of fields in support of the MI Programme portfolio.The role offers flexibility to work remotelyResponsibilitiesProvide expert advanced modelling and data analytics support to all teams in Manufacturing Intelligence organization and in support of project execution at manufacturing sites.Translate business requirements into tangible solution specifications and high quality, on time deliverablesProvide data manipulation/transformation, model selection, model training, cross-validation and deployment support at scaleSupport development, testing, deployment, and qualification of process soft sensor modelsSupport development, testing & validation of hybrid models using first-principle mathematical modelling combined with Machine learningWork with manufacturing sites stakeholders, analyze & solve business problems using Machine learning & Artificial Intelligence capabilities & support deployment on cloud platformStay abreast of industry 4.0 trends and developments in AI/ML and work with other MI teams to pilot new advances to drive value for Pfizer Global Supply (PGS)Desired profile of the candidateMinimum 3 years Data Science experience for candidates with Post-graduation degree (MS/MTech) and 1 year for Ph.Ds. with thesis/project in Chemical, Bioprocess Modeling or other relevant fieldFirst principle and hybrid-model development (including soft sensors), background in reaction kinetics, mass & heat transfer or Bioprocess modeling (must have)Experience of working on Science/Physics informed machine/deep learning models (must have)Data science/ML and AI experience with hands on Scikit-Learn, TensorFlow and PyTorch libraries exposure. (must have)Process Analytical Technology (PAT), process modelling, RTR, Advanced Process Control (APC), model predictive control (MPC) with hands-on experience on SIMCA, PharmaMV, AspenTech or similar tools (good to have)Continuous process verification (CPV) & exposure on Tibco Informa or similar platform (good to have)Deployment of Python codes on cloud platform for real-time execution (good to have)Intelligent and dynamic scheduling platforms experienceTechnical knowledge of pharmaceutical manufacturing unit operations and experience of delivery of innovative solutions in a regulated environmentQualificationMasters or PhD in Chemical Engineering, Bioprocess Modeling , Data Science, Statistics, Applied Mathematics, Computer Science or related technical field.Attributes:Ability to collaborate effectively internally and with cross-functional teams and key stakeholders.High level of innovative ability, agility with high energy for continuous learning.Highly self-motivated and results focused, with track record of value delivery through technical innovationAbility to communicate effectively at multiple levels covering project technical details or progress and impact updates to key stakeholdersManage multiple projects and priorities efficientlyLocation: FlexiblePfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.Medical