Senior Scientist: Process Modeling and Hybrid Modelling
The Manufacturing Intelligence (MI) team within Pfizer’s Global Technology & Engineering (GT&E) is responsible for driving the development and implementation of advanced analytics including AI/ML, soft sensor, advanced process control, and process condition monitoring solutions in support of manufacturing and future capabilities in Pfizer Global Supply (PGS).As a member of MI, this role will have the opportunity to develop and implement advanced analytics, real-time soft sensors, machine learning, advanced process control and IIoT solutions/capabilities in manufacturing settings to achieve actionable insights and enable continued improvement for pharmaceutical manufacturing and quality operations.
Responsibilities
- Technical contribution to high-impact projects that require data analytics, advanced modeling, and optimization expertise.
- Identify high value opportunities for applying Advanced Analytics, Advanced Process Control (APC), Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT), Generative AI and develop and deploy innovative fit-for-purpose solutions in manufacturing environment
- Drive development of mathematical and machine learning models and support GMP implementation of such analytics solutions
- Apply engineering principles, modeling tools, and experimental skills using data-rich lab/pilot/manufacturing equipment to improve process understanding and facilitate real-time process monitoring and control
- Collaborate with cross-functional teams and key stakeholders, effectively communicate progress to management, and drive project progress in a timely manner.
Basic Qualifications
- B. Tech computer science is preferred.
- Expert-level knowledge in Python is a must. Experience in any of the following languages is a plus: R, Matlab, JavaScript.
- Ability to perform data engineering on real world big-data ranging from structured time-series datasets with thousands of features.
- Track record in applying data science and machine learning methodologies to real-world data to generate insight and support decision making.
- Ability to work collaboratively in diverse cross-functional teams on innovative solutions and tools with an open attitude towards fast learning.
- Knowledge of upstream and downstream Biopharmaceutical Manufacturing
- Demonstrated experience of story-telling to technical experts and non-technical stakeholders
- Independent, self-motivated personality with excellent oral and written communication skills
Preferred Qualifications
- Expertise in first principles (thermodynamics, reaction modeling, heat transfer, mass transfer principles), hybrid modeling. Ability to develop practical process models for real-time applications is a strong plus.
- Experience deploying Interpretable Machine Learning or Explainable AI and knowledge of Shapley values and plots
- Experience in cloud-based code development and deployment environments such as AWS SageMaker.
- Familiarity with cloud computing based data-warehouses such as Snowflake or Redshift, and relational SQL databases.
- Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as DeltaV and ASPEN.
- Experience in data visualization and real-time GUIs using Streamlit, Plotly, Spotfire, etc.
- Knowledge of Cell Culture, Fermentation and Vaccines Conjugation Work Location Assignment: Flexible
Work Location Assignment: Remote
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.Information & Business Tech
