Senior Scientist – Manufacturing Intelligence | Pfizer | Chennai

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Job Overview

  • Date Posted
    February 5, 2023
  • Location (State / UT)
  • Expiration date
    --
  • Experience
    3 Years
  • Gender
    Any
  • Desired Qualification
    Master’s Degree, Doctorate Degree

Job Description

The Manufacturing Intelligence organization within Pfizer’s 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 identifies and delivers 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 Science) is responsible for providing expert advanced data analytics and modeling 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. 

Responsibilities:

  • Provide expert advanced modeling and data analytics support to all teams in the Manufacturing Intelligence organization and in support of project execution at manufacturing sites.
  • Translate business requirements into tangible solution specifications and high-quality, on-time deliverables
  • Provide data manipulation/transformation, model selection, model training, cross-validation, and deployment support at scale
  • Support development, testing, deployment, and qualification of process soft sensor models
  • Support development, testing & validation of hybrid models using first-principle mathematical modeling combined with Machine learning
  • Work with manufacturing sites stakeholders, analyze & solve business problems using Machine learning & Artificial Intelligence capabilities & support deployment on a cloud platform
  • Stay 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 candidate:

  • Minimum 3 years of Data Science experience for candidates with a Post-graduation degree (MS/MTech) and 1 year+ for Ph.Ds. with a thesis/project in Chemical, Bioprocess Modeling, or other relevant fields
  • The first principle and hybrid-model development (including soft sensors), background in reaction kinetics, mass & heat transfer, or Bioprocess modeling (must have)
  • Experience 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 modeling, 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 a cloud platform for real-time execution (good to have)
  • Intelligent and dynamic scheduling platforms experience
  • Technical knowledge of pharmaceutical manufacturing unit operations and experience in the delivery of innovative solutions in a regulated environment

Qualifications

  • Masters or Ph.D. 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, and agility with high energy for continuous learning.
  • Highly self-motivated and results-focused, with a track record of value delivery through technical innovation
  • Ability to communicate effectively at multiple levels covering project technical details or progress and impact updates to key stakeholders
  • Manage multiple projects and priorities efficiently